{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1a31ef52",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import pymysql"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eb32d765",
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "1、计算微博来源top10 -> 饼图\n",
    "2、微博用户性别占比 -> 饼图\n",
    "3、微博转发数、点赞数、评论数topN -> 柱状图\n",
    "4、根据微博发布时间统计哪个时间段的微博数量最多 -> 折线图\n",
    "5、根据评论发布时间统计哪个时间段的评论数量最多 -> 折线图\n",
    "6、用户粉丝数量topN -> 柱状图\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2f17e58c",
   "metadata": {},
   "outputs": [],
   "source": [
    "conn = pymysql.connect(user='root',password='123456',host='master',port=3306,database='weiboSpider')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "47c024be",
   "metadata": {},
   "outputs": [],
   "source": [
    "weiboDF = pd.read_sql('select * from weiboArticle',con=conn)\n",
    "commentDF = pd.read_sql('select * from comment',con=conn)\n",
    "userDF = pd.read_sql('select * from user',con=conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c7c98256",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th>id</th>\n",
       "      <th>screen_name</th>\n",
       "      <th>created_at</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>mid</th>\n",
       "      <th>attitudes_count</th>\n",
       "      <th>comments_count</th>\n",
       "      <th>reposts_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2823776192</td>\n",
       "      <td>王故里</td>\n",
       "      <td>Tue Oct 26 11:05:37 +0800 2021</td>\n",
       "      <td>iPhone 13 Pro Max(远峰蓝色)</td>\n",
       "      <td>&lt;a  href=\"https://m.weibo.cn/search?containeri...</td>\n",
       "      <td>4696505108139675</td>\n",
       "      <td>9567</td>\n",
       "      <td>623</td>\n",
       "      <td>1086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2808518423</td>\n",
       "      <td>飛諺評談</td>\n",
       "      <td>Fri Oct 29 09:19:48 +0800 2021</td>\n",
       "      <td>某评论员的iPhone客户端</td>\n",
       "      <td>&lt;a  href=\"https://m.weibo.cn/search?containeri...</td>\n",
       "      <td>4697565642359968</td>\n",
       "      <td>42</td>\n",
       "      <td>21</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1644489953</td>\n",
       "      <td>南方都市报</td>\n",
       "      <td>Fri Oct 29 17:22:00 +0800 2021</td>\n",
       "      <td>微博 weibo.com</td>\n",
       "      <td>【&lt;a  href=\"https://m.weibo.cn/search?container...</td>\n",
       "      <td>4697686990652953</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5131917830</td>\n",
       "      <td>刷野制霸</td>\n",
       "      <td>Fri Oct 29 17:21:43 +0800 2021</td>\n",
       "      <td>Android</td>\n",
       "      <td>&lt;a  href=\"https://m.weibo.cn/search?containeri...</td>\n",
       "      <td>4697686920661879</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2426194884</td>\n",
       "      <td>封跃平律师</td>\n",
       "      <td>Fri Oct 29 15:42:29 +0800 2021</td>\n",
       "      <td>微博视频号</td>\n",
       "      <td>&lt;a  href=\"https://m.weibo.cn/search?containeri...</td>\n",
       "      <td>4697661947775466</td>\n",
       "      <td>66</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id screen_name                      created_at  \\\n",
       "0  2823776192         王故里  Tue Oct 26 11:05:37 +0800 2021   \n",
       "1  2808518423        飛諺評談  Fri Oct 29 09:19:48 +0800 2021   \n",
       "2  1644489953       南方都市报  Fri Oct 29 17:22:00 +0800 2021   \n",
       "3  5131917830        刷野制霸  Fri Oct 29 17:21:43 +0800 2021   \n",
       "4  2426194884       封跃平律师  Fri Oct 29 15:42:29 +0800 2021   \n",
       "\n",
       "                    source                                               text  \\\n",
       "0  iPhone 13 Pro Max(远峰蓝色)  <a  href=\"https://m.weibo.cn/search?containeri...   \n",
       "1           某评论员的iPhone客户端  <a  href=\"https://m.weibo.cn/search?containeri...   \n",
       "2             微博 weibo.com  【<a  href=\"https://m.weibo.cn/search?container...   \n",
       "3                  Android  <a  href=\"https://m.weibo.cn/search?containeri...   \n",
       "4                    微博视频号  <a  href=\"https://m.weibo.cn/search?containeri...   \n",
       "\n",
       "                mid  attitudes_count  comments_count  reposts_count  \n",
       "0  4696505108139675             9567             623           1086  \n",
       "1  4697565642359968               42              21             13  \n",
       "2  4697686990652953                0               0              0  \n",
       "3  4697686920661879                0               0              0  \n",
       "4  4697661947775466               66               8             15  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weiboDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "640b3103",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mid</th>\n",
       "      <th>user_id</th>\n",
       "      <th>comment_id</th>\n",
       "      <th>text</th>\n",
       "      <th>created_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4697676673975714</td>\n",
       "      <td>7306650050</td>\n",
       "      <td>4697687385442479</td>\n",
       "      <td>200万就这样了，请明星代言可不止200万吧？</td>\n",
       "      <td>Fri Oct 29 17:23:34 +0800 2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4697676673975714</td>\n",
       "      <td>5822570862</td>\n",
       "      <td>4697682314265796</td>\n",
       "      <td>这就是有预谋的营销活动，很快就会成为一个营销策划的经典案例&lt;span class=\"url-...</td>\n",
       "      <td>Fri Oct 29 17:03:24 +0800 2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4697676673975714</td>\n",
       "      <td>2485834535</td>\n",
       "      <td>4697686537668682</td>\n",
       "      <td>我去，才知道元气森林不是日本品牌&lt;span class=\"url-icon\"&gt;&lt;img al...</td>\n",
       "      <td>Fri Oct 29 17:20:11 +0800 2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4697676673975714</td>\n",
       "      <td>2719414532</td>\n",
       "      <td>4697680498656935</td>\n",
       "      <td>&lt;span class=\"url-icon\"&gt;&lt;img alt=[笑cry] src=\"ht...</td>\n",
       "      <td>Fri Oct 29 16:56:12 +0800 2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4697299269192394</td>\n",
       "      <td>1401198487</td>\n",
       "      <td>4697304789157589</td>\n",
       "      <td>看情况吧，如果对面是普通商家我就退了。就这个例子来说，元气森林那么爱营销，我肯定不退</td>\n",
       "      <td>Thu Oct 28 16:03:16 +0800 2021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                mid     user_id        comment_id  \\\n",
       "0  4697676673975714  7306650050  4697687385442479   \n",
       "1  4697676673975714  5822570862  4697682314265796   \n",
       "2  4697676673975714  2485834535  4697686537668682   \n",
       "3  4697676673975714  2719414532  4697680498656935   \n",
       "4  4697299269192394  1401198487  4697304789157589   \n",
       "\n",
       "                                                text  \\\n",
       "0                            200万就这样了，请明星代言可不止200万吧？   \n",
       "1  这就是有预谋的营销活动，很快就会成为一个营销策划的经典案例<span class=\"url-...   \n",
       "2  我去，才知道元气森林不是日本品牌<span class=\"url-icon\"><img al...   \n",
       "3  <span class=\"url-icon\"><img alt=[笑cry] src=\"ht...   \n",
       "4         看情况吧，如果对面是普通商家我就退了。就这个例子来说，元气森林那么爱营销，我肯定不退   \n",
       "\n",
       "                       created_at  \n",
       "0  Fri Oct 29 17:23:34 +0800 2021  \n",
       "1  Fri Oct 29 17:03:24 +0800 2021  \n",
       "2  Fri Oct 29 17:20:11 +0800 2021  \n",
       "3  Fri Oct 29 16:56:12 +0800 2021  \n",
       "4  Thu Oct 28 16:03:16 +0800 2021  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "commentDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cef69dbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>screen_name</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>follow_count</th>\n",
       "      <th>gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2823776192</td>\n",
       "      <td>王故里</td>\n",
       "      <td>103万</td>\n",
       "      <td>1673</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2808518423</td>\n",
       "      <td>飛諺評談</td>\n",
       "      <td>8.3万</td>\n",
       "      <td>235</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1644489953</td>\n",
       "      <td>南方都市报</td>\n",
       "      <td>1868.5万</td>\n",
       "      <td>705</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5131917830</td>\n",
       "      <td>刷野制霸</td>\n",
       "      <td>125</td>\n",
       "      <td>116</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2426194884</td>\n",
       "      <td>封跃平律师</td>\n",
       "      <td>401.3万</td>\n",
       "      <td>2184</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id screen_name followers_count follow_count gender\n",
       "0  2823776192         王故里            103万         1673      m\n",
       "1  2808518423        飛諺評談            8.3万          235      m\n",
       "2  1644489953       南方都市报         1868.5万          705      m\n",
       "3  5131917830        刷野制霸             125          116      m\n",
       "4  2426194884       封跃平律师          401.3万         2184      m"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "userDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e99ba3d0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 926 entries, 0 to 925\n",
      "Data columns (total 9 columns):\n",
      " #   Column           Non-Null Count  Dtype \n",
      "---  ------           --------------  ----- \n",
      " 0   id               926 non-null    int64 \n",
      " 1   screen_name      926 non-null    object\n",
      " 2   created_at       926 non-null    object\n",
      " 3   source           926 non-null    object\n",
      " 4   text             926 non-null    object\n",
      " 5   mid              926 non-null    object\n",
      " 6   attitudes_count  926 non-null    int64 \n",
      " 7   comments_count   926 non-null    int64 \n",
      " 8   reposts_count    926 non-null    int64 \n",
      "dtypes: int64(4), object(5)\n",
      "memory usage: 65.2+ KB\n"
     ]
    }
   ],
   "source": [
    "weiboDF.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e758ed27",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                 0\n",
       "screen_name        0\n",
       "created_at         0\n",
       "source             0\n",
       "text               0\n",
       "mid                0\n",
       "attitudes_count    0\n",
       "comments_count     0\n",
       "reposts_count      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weiboDF.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "dc7cccbe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['<a  href=\"https://m.weibo.cn/search?containerid=231522type%3D1%26t%3D10%26q%3D%23%E5%A6%82%E4%BD%95%E7%9C%8B%E5%BE%85%E5%85%83%E6%B0%94%E6%A3%AE%E6%9E%97%E8%A2%AB%E8%96%85%E7%BE%8A%E6%AF%9B%23&extparam=%23%E5%A6%82%E4%BD%95%E7%9C%8B%E5%BE%85%E5%85%83%E6%B0%94%E6%A3%AE%E6%9E%97%E8%A2%AB%E8%96%85%E7%BE%8A%E6%AF%9B%23&luicode=10000011&lfid=100103type%3D1%26q%3D%E5%85%83%E6%B0%94%E6%A3%AE%E6%9E%97\" data-hide=\"\"><span class=\"surl-text\">#如何看待元气森林被薅羊毛#</span></a> 元气森林店铺秒杀活动设置错误，有人表示甚至一次性买了三万瓶，官方运营哭诉给公司造成了200万的损失，这样的撸货薅羊毛会发货嘛，你觉得元气森林是无心之举还是刻意营销？？？ '],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weiboDF.text[:1].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e84f84ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "weiboDF.text = weiboDF.text.replace({r'<[^>]+>':''},regex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1dfd380e",
   "metadata": {},
   "outputs": [
    {
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       "      <th>0</th>\n",
       "      <td>2823776192</td>\n",
       "      <td>王故里</td>\n",
       "      <td>Tue Oct 26 11:05:37 +0800 2021</td>\n",
       "      <td>iPhone 13 Pro Max(远峰蓝色)</td>\n",
       "      <td>#如何看待元气森林被薅羊毛# 元气森林店铺秒杀活动设置错误，有人表示甚至一次性买了三万瓶，官...</td>\n",
       "      <td>4696505108139675</td>\n",
       "      <td>9567</td>\n",
       "      <td>623</td>\n",
       "      <td>1086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2808518423</td>\n",
       "      <td>飛諺評談</td>\n",
       "      <td>Fri Oct 29 09:19:48 +0800 2021</td>\n",
       "      <td>某评论员的iPhone客户端</td>\n",
       "      <td>#元气森林再次回应运营事故#果然不出所料，最终可能还是演变成了事件营销。元气森林第一步为14...</td>\n",
       "      <td>4697565642359968</td>\n",
       "      <td>42</td>\n",
       "      <td>21</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1644489953</td>\n",
       "      <td>南方都市报</td>\n",
       "      <td>Fri Oct 29 17:22:00 +0800 2021</td>\n",
       "      <td>微博 weibo.com</td>\n",
       "      <td>【#元气森林事故订单额达千万# 称价格设错请顾客退款！律师：其无权单方面变更合同】近日，元气...</td>\n",
       "      <td>4697686990652953</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5131917830</td>\n",
       "      <td>刷野制霸</td>\n",
       "      <td>Fri Oct 29 17:21:43 +0800 2021</td>\n",
       "      <td>Android</td>\n",
       "      <td>#元气森林向14万下单用户每人赠送一箱饮料# 有报道说事故订单的损失不止200多万，可能达数...</td>\n",
       "      <td>4697686920661879</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2426194884</td>\n",
       "      <td>封跃平律师</td>\n",
       "      <td>Fri Oct 29 15:42:29 +0800 2021</td>\n",
       "      <td>微博视频号</td>\n",
       "      <td>#元气森林商业信誉如何挽回# 原价79元气泡水仅卖3.5元被买爆，有人一次下单3万箱，元气森...</td>\n",
       "      <td>4697661947775466</td>\n",
       "      <td>66</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id screen_name                      created_at  \\\n",
       "0  2823776192         王故里  Tue Oct 26 11:05:37 +0800 2021   \n",
       "1  2808518423        飛諺評談  Fri Oct 29 09:19:48 +0800 2021   \n",
       "2  1644489953       南方都市报  Fri Oct 29 17:22:00 +0800 2021   \n",
       "3  5131917830        刷野制霸  Fri Oct 29 17:21:43 +0800 2021   \n",
       "4  2426194884       封跃平律师  Fri Oct 29 15:42:29 +0800 2021   \n",
       "\n",
       "                    source                                               text  \\\n",
       "0  iPhone 13 Pro Max(远峰蓝色)  #如何看待元气森林被薅羊毛# 元气森林店铺秒杀活动设置错误，有人表示甚至一次性买了三万瓶，官...   \n",
       "1           某评论员的iPhone客户端  #元气森林再次回应运营事故#果然不出所料，最终可能还是演变成了事件营销。元气森林第一步为14...   \n",
       "2             微博 weibo.com  【#元气森林事故订单额达千万# 称价格设错请顾客退款！律师：其无权单方面变更合同】近日，元气...   \n",
       "3                  Android  #元气森林向14万下单用户每人赠送一箱饮料# 有报道说事故订单的损失不止200多万，可能达数...   \n",
       "4                    微博视频号  #元气森林商业信誉如何挽回# 原价79元气泡水仅卖3.5元被买爆，有人一次下单3万箱，元气森...   \n",
       "\n",
       "                mid  attitudes_count  comments_count  reposts_count  \n",
       "0  4696505108139675             9567             623           1086  \n",
       "1  4697565642359968               42              21             13  \n",
       "2  4697686990652953                0               0              0  \n",
       "3  4697686920661879                0               0              0  \n",
       "4  4697661947775466               66               8             15  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weiboDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f356661a",
   "metadata": {},
   "outputs": [],
   "source": [
    "source_cnt = weiboDF.groupby('source')['id'].count().reset_index().rename(columns={'id':'cnt'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9a67f8d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>source</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td></td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>#兵来兵住#HarmonyOS设备</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>456...Android</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Android</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Find X3 Pro MARS</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              source  cnt\n",
       "0                      83\n",
       "1  #兵来兵住#HarmonyOS设备    1\n",
       "2      456...Android    1\n",
       "3            Android   27\n",
       "4   Find X3 Pro MARS    1"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "source_cnt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "3d5a4834",
   "metadata": {},
   "outputs": [],
   "source": [
    "source_top10 = source_cnt[source_cnt.source != ''].sort_values('cnt',ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "a87b6a54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>source</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>iPhone客户端</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>微博视频号</td>\n",
       "      <td>96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>微博 weibo.com</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Android</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>微博国际版</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           source  cnt\n",
       "86      iPhone客户端  139\n",
       "165         微博视频号   96\n",
       "161  微博 weibo.com   46\n",
       "3         Android   27\n",
       "162         微博国际版   25"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "source_top10.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "93f6f026",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "d804641a",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 解决中文显示问题-设置字体为黑体\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号'-'显示为方块的问题"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "6b74ba3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QQkgbUYEihBBCCGkjKlCEEEJIOzQvdnmh2tpadolD/6J5RXDScdGNUUIIIaSNFi5c6GOxWFifPn0aPvzwQ785c+aci4uLM8yYMUO/adOmk83HzZ07N/j666+vio2NNRgMBrZ8+XIvk8nETCYTGzVqVO3o0aPrtFotPc3VAVGBIoQQ0qH1+aJPvC3Pd/iew1dcFmHDhg3aLVu2uC9cuDD/8ccfD3Vzc5M+/fRTn+nTp1fo9XpDamqqOjAw0BwWFmYGAJVKxdetW+eel5enSk9Pd+Wcs4EDB9bt2rXLLTo62hgbG2u80vVa47777gtbunTpGcBa2saOHVtzww031FztecnlUYEihBBC2mD8+PG1ISEhplmzZkWkpaVpBUHggiDAw8ND0mg0fNasWd0WLVqUV1NTIxQVFSnT09M1FRUV4ooVK3w55+Cco6CgQBUTE9Ngi/IEAM3liTgOzYEihBBC2kAURbzwwguBM2fOLFuwYEHeq6++embJkiWnt27d6v7aa68V9urVq37s2LF1J0+edCkqKlJmZWWpGxsbhbCwMINerzdEREQYevfuXS+K4mVv3fXu3btnQUGBwsfHp19ubq5y9OjR0TU1NcLEiRMjBw0aFHv33XeHX3j8hVu2AMBbb70VkJCQEHvDDTdEms1mAMA999wTFh8fHzt27NjokpKSS667IEkS7r777vCBAwf2SExMjM3Ly1Nc6r2JiYmxN954Y7ehQ4fGDB06NOb+++8Pu+pvbAdDBYoQQghpgxUrVug2btzoqdfrjT169DDExsY2AoAgCDh48KBakiQGADfeeGPNwIED62+//faKgIAAU25urktOTo5Lbm6uy+HDh10BXHbCeXh4uGHNmjUe/fr1q1u7dq1Hv3796t9++23fuLi4xn379mWfPXtWuWfPHs3l3j9w4MC61NTUbA8PD8uKFSs8V6xYoTMYDML+/fuzb7rppop58+YFXu5rs1gs7MCBA0f/+c9/Fu/cudPtcu994403CoqKilTr168/kZGRcdksnRXdwiOEEELaIDo62jBz5swSd3d3afbs2RE1NTXinDlzip999tnCzz//3CcmJqbx4veEhYWZFi9enGc2m2GxWFh5ebloNBovW6D69+9f//3333tPnDixatWqVV6zZs0q3bBhg8e+ffu027dvd6+urhZzc3OVgwcPbrjU+4cOHVoHAAMGDKg7ceKEi8ViQWJiYh0AjBgxom7NmjWel3rfkSNH1AkJCXUAcPvtt1dZLBbMmzcv4FLvjY2NNfr7+5t0Op3EOW/V04edCRUoQgghpA0SEhIaV69eLQGAh4eHed68eYW7d+92HT9+fO39998fuXnz5qMXHl9XVyfMmzcvRKVSSc0rlhcUFKg8PDwsaWlprh9//HH+xdeIj4+vf+edd4IWL1585rnnngtbsmRJXk5OjioxMbFuzpw5ZStWrNBFRkZedv5Uamqq67Rp06oPHTrkOm7cuGq1Ws1Xr17tCaB027Ztbj179vxLyQOAnj17NqakpOgA4IMPPvDOysrSDB8+vPbi9+7du1fbzm9fp0EFihBCCGkjzjkyMzPVrq6uUnl5ubhnzx5tbW2tGBISYvztt9+08fHx5wuKm5ubdPjw4SMPPPBA6HXXXVc9ffr06rlz5wZPnTq1ctSoUfWXOv/QoUPrg4KCjD169DB4e3ubY2JijE888UTpjBkz9MuWLfN1d3e3fP/996cul2/nzp3uCQkJOh8fH9Odd95ZqVQqsW7dOo/4+PhYnU5nWbly5emzZ8+Kjz/+eOjKlStzm993++23V/3888+6QYMGxWo0GmnlypWng4ODzRe/d9KkSdG2/Y52PLSZMCGEkA7FGTYTnjt3bnCPHj0aBg0a1NCzZ0/D7bffrh81alTNnDlzSh988MGwyZMnV06dOrVmzpw5wZMnT64aN25cXUFBgaK8vFw8duyYyzPPPBO2bt264zExMTZ5Cq8rcLbNhKlAEUII6VCcoUBdzGKxtHpD4bKyMpFzDl9fX1qOvA2crUDRLTxCCCHkKrW2PAGAj48PFadOgJYxIIQQQghpIypQhBBCCCFtRAWKEEIIIaSNaA4UIYSQDu1Ij5423Uy459EjV9xMGADOnj0rduvWrW9paWmaq6vrFZ/Gau/mvhduEGyL8xHbogJFCLEJfVKKCMAdgEfThzsANwDqy3wIAEwAjAAMTf+88NeXeq351+U5CybVOuhLI+Qv1q5d62E0Gtn69evdb7755mp7XIM2CHZuVKAIIVekT0rxARAGIPSCj+bfBwPwhLUwuTo4Vx2AswCKmz4u/PWffp+zYJLBkdlI57dhwwbdzJkzS37++WeP7du3a00mE9u9e7e2pqZG/OWXX45pNBo+ZcqUKIvFAs45Gzt2bA1g3fR3wIABdZmZmZrt27cfb2hoYNOnT9cXFxergoKCjN98802OWq3mzcfu3bs3GwBKSkrES52PyIcKFCFdWNOoUfemjwuLUfOvQwA46yahbgAimz6uSJ+UUgVrmcoHcBTAkeaPnAWTiuwZknRO+/fvd9u5c2f2mDFjYiZNmlR56tQpl9TU1Oz//Oc/AT///LPHmTNnVBMnTqx8/vnnzw0bNqx78/vS09PdHnnkkbNLlizJB4CmDYIbfvzxx9NPPvlk0KJFi3yfeeaZkouv98477/hd6nxEPlSgCOki9EkpfgD6Aejb9NEHQByst9M6O13TRyyAcRd+Qp+UUomLShWALAA5OQsmSY6NSdrKYDAobX3OiooK99raWm1YWFjRqVOnwsPDwwuOHz8e3bNnz+yjR492r6ioKKisrFRMmTIlqrCwUJWfn6+8++67ywDA39/fbDQa2enTp1UzZsyoAIABAwac366le/fuDffcc09l8++zsrI0t9xySwVg3QC4eR+6i13ufEQ+VKAI6WT0SSkusBajC4tSXwABcuZyYp4AhjR9XKhRn5SSjT8KVSqAXTkLJlU5Nl7Hwhh7h3P+RNOvkwHcBqAE1vludwOYDWAz53yzLa5nNBptXqBcXV0bJUkSjUajAgDq6uo0nHPU1NS4SpIkpKSkuM+ZM6c4OTn57Jw5c4L/97//+c6cObP8wnNEREQYMzIy1JMnT645fPiw69/+9rfqpnP/qZT36tWrYefOndqpU6fW7Ny5U9urV6+GS2W63PmIfKhAEdLB6ZNSYgGMBjAKwAAAMaD/tm1BDeuIXb8LXpP0SSmZAHY0f+QsmHRajnDOqrk8XeBlzvlXjLG7ADwG60MANqNUKk22PB8AFBUVBTDGYDQaVd7e3hX19fUaLy+v8traWjcvL6/yX3/91evNN988AwDjx4+vyc7O/sso7uOPP146derUyDVr1nibzWZ2uWs98cQTpdOnT9cPGjQoNjg42Pjf//73kreUW3s+4ji0Fx4hHUxTYRrT9DEaQJCceQiKcEGhAnAwZ8Eks7yR5MMY28w5H9P062QAJ5oK1GMAvGB9+lIJYASst1UnAqgA8DmsDyXkA5gF4LlLHFcN4MtNmzbdEBkZWd2tW7c8AKiqqtLm5uZGqFQqY0hISIEgCFJeXl54dHT0SaVSeX7bFKPRqMjNzQ3v3r37qYtzHzp0qHffvn0zamtrNUajUSVJEjOZTMqamhp3SZJEzjljjHHOOfz9/c/5+PjQSKSD0V54hJA2ocLk9IIA3NL0AQD1+qSUvfijUG3r4ksu/JsxNhvAGQAPA/gngGjO+WjG2DMAxgLwBpDBOb+dMTYPwH1N7734OH8AGb6+voNMJpOutrZWo9VqG5RKpal79+4nACA7OzuWcy7o9fpTF5anZrW1te5ZWVmxF79uMpmUACAIglRRUeHp4uJi0Gq1dUFBQSVN542KjY09aetvDum4qEAR4mT0SSndYZ3oPAbWwhQoayDSVq74o/ACgEGflPI7gB8B/JizYFJXW9vnZc75V82/YYwBwJdNvz0HQAXrnL1VTa/tAfA3WEelLj4uFsCw0tLSwICAAMloNCqrqqrEqqoqXWNjoxoAQkND85RKpbmsrMynsLAwhDEm+fr6lvj7+5ebzWbR3d29Kjo6OufikIcPH47jnEOj0RgMBoOac84CAwPPZWRkxFksFlEURXNaWlpfxhiPiIjI8fT0pGUEujgqUIQ4AX1SykAANwOYBqCHzHGIbbnAevtpIoD39EkpabCWqbUA9ucsmNQV51HUXfT7TFgn8W9q+mcmrLfzLj4uG8BeX1/fecHBwSYXFxej2WxWqNXqBovFItbV1bmVlJT4Nx9sMBhcevTocUQQBAkA6urqXDUazSUnacfFxR1pKncIDQ3NLy4uDmhsbHRRq9X1Li4uBp1OV11aWuqjUqmMjLGu+O+MXIQKFCEy0CelMADDYC1NNwPQyxqIOFL/po//A1CkT0r5CdYy9WvOgkmX/OHeBXwC4HPG2FZYb/X9F9Y5UBf7GMBnpaWlgWq1ujEqKuqUm5tbIwDk5uZqQkND8y8cGTpy5EisRqMxNBejiooKr9DQ0IJLBRBFkQPAuXPnvMvLy32USqXxEk/40eRtch5NIifEQfRJKQpYb+vcDGAqaC4T+bN6AL/CWqZ+ylkwqVjmPE4rPT09p1+/fqUXvpaTkxNaW1vrIYri+XlPDQ0Nmr59+x5SKBRSWVmZrrS01LeleUxGo1GhUCjMgiAAAE6cONEtODi4UKlUmmtqarTnzp3z1+v1uWq12miXL45clrNNIqcCRYgdNa3JdC2st+ZuBOAjbyLSQXAAWwB8BuC7nAWTaOHEC1yqQEmSBMZY8xyrvzCbzaLFYhFcXFyuatkDi8UiiKIoNV+zuWg1q62tZVqt9oo/WC0WC0RRvJoYXZKzFSi6hUeIHeiTUq4BcD+AybBuqktIWzD8MRH9XX1SyrcAPs9ZMGmbnKGc1XsP/RZvy/M98uHY/Zf7XHN5WrhwoY/FYmF9+vRp+PDDD/3mzJlzLi4uzjBjxgz9pk2bTgLA3Llzg6+//vqq2NhYg8FgYMuXL/cymUzMZDKxUaNG1Y4ePbpOo9FwT0/P/j179rzk7dsjR45oSkpK0tPT09WTJk2KCQkJMTDG8OCDD5778ssvfZuLmFqtln777bcTADBx4sTIr776KnfWrFnhS5cuzRszZkyMWq2WPD09zVqtVvrkk0/y/Pz8/vKEImkbKlCE2EjTVimzADwA695yhNiCO6yP9d+nT0o5AeALAF90waf5nMaGDRu0W7ZscV+4cGH+448/Hurm5iZ9+umnPtOnT6/Q6/WG1NRUdWBgoBkAVCoVX7dunXteXp4qPT3dlXPOBg4cWLdr1y636OhoY2xsrDE2NrZh165d2QDOj0xJkgRJkjBs2LBYpVLJlUolHz16dNVtt91WvnPnTu3s2bPLH3roofLm4xsbG88PvXHOmaurq6RSqbhKpeKxsbENq1atynH4N6qTowJFyFVomgw+DtbtKabA+qg1IfYSDeBFAPP1SSm/wbr45KouPPlcFuPHj68NCQkxzZo1KyItLU0rCAIXBAEeHh6SRqPhs2bN6rZo0aK8oqIiZXp6uqaiokJcsWKFL+ccnHMUFBSoYmJiGmJjY40AIAgCVq5cqfvggw/8CwsLVe7u7hYPDw/LnXfeWQZYS1XzrcnffvvN4/rrr69qfr2ZUqnkJpMJSqUSCoXi/C1ESZJQVlam2LBhgxYAFAoFHzdu3MVPN5J2oAJFSDvok1ICYB0VeABApMxxSNcjABjf9FGlT0r5BtZbfDvljdU1iKKIF154IXDmzJllM2bMKBdFEd7e3ubnn38+ZPfu3dn33nuvoq6uTigqKlJmZWWpvby8LGFhYQZBECBJEsLCwowWy5/voN12221Vt956a9WLL74YkJiYWD9hwoQaQRDw6aef+l143J49e7SPPvpoyZAhQ2JFUcTRo0c13bt3bxAEAffee2/JI488Ut7Q0CCMGTMmhnOOJUuW+Jw+fVr99NNPh44fP75648aNusOHDx9x6Desk6ICRUgr6ZNSBADXAXgQ1gnhNt/ElJB20MH6Z/JBfVLKEQDvAPgyZ8GkRllTdWIrVqzQbdy40fPRRx8tEQQBgiDwkpIShSAIOHjwoFqSJHbjjTfW/P777+5Tp06tPHjwoCY3N9eFMQbOOSorKxVxcXF/GjXcu3ev5sknnwwtKipSrV69Wnr55ZctCxYsyL/42jfddFP5pk2btNu2bTumVqv5iBEjYtatW3dCEAS4u7tLwJ/nQ+Xl5SnS09Ndy8vLFfPnzy8+evToX/btI+1DBYqQFjTNbfo7rJPC9fKmIeSKegJYAuBFfVLKuwDey1kwqVzmTJ1OdHS0YebMmSXu7u7S7NmzI2pqasQ5c+YUP/vss4Wff/65T0xMzJ/Ka1hYmGnx4sV5ZrMZFouFlZeXi0aj8U+PCw4dOrRh586dx59//vmAvn37NqxatcpzxIgRf3n6cvr06ZUPP/xweEFBgSooKMgEAN98841u06ZNHitXrswFgMrKSjExMTG2rq5O+OCDD3L9/f1NZ8+eVe7du1fTq1cvut1rI1SgCLkMfVJKGICnYb1Np5E5DiFt4Q/gBQBJ+qSUpQDeylkw6bTMmTqNhISExtWrV0sA4OHhYZ43b17h7t27XcePH197//33R27evPlo87F1dXXCvHnzQlQqldQ8Z6mgoEDl4eFhSUtLc/3444/zAeDpp58O2rNnj7a+vl7YtGmTTqlUSk8++WTwhdetqakRp0yZEn3//feXfPnll767d+8++t1333nffPPN1a+88kpwRkaGS+/evQ0KhQI7d+7MnjBhQlR6eromOjrawDnHK6+8Evjvf/+7yIHfqk6NChQhF2naiy4JwN2g23SkY3MF8CiAf+iTUr4H8HrOgkn7ZM5kc1dadsBeOOfIzMxUu7q6SuXl5eKePXu0tbW1YkhIiPG3337TxsfHNwKAm5ubdPjw4SMPPPBA6HXXXVc9ffr06rlz5wZPnTq1ctSoUfWAdV2o119//ZLFJjExMdZiscBiscDd3d2ydevW7C+++ML7b3/7W6VWq+Vms5kpFAr+2GOPnf3666+9nn766XPNW81wzrFp0yaP1157rcDDw8OybNkyv4EDB9KtXRuhAkVIE31SSl9Yt4+4FdZJuoR0FiKA6QCm65NStgB4HcDPXXQfPpswGAxCfX09mz9/flHPnj0Nq1at8goPDzdmZmZmPfjgg2Fr1qxxt1gsMJlMDADmz59fXF5eLn7//fceP/zwg9dDDz1UCljL07FjxzSJiYmxl7rOkSNHNCaTiVksFgYAAQEBlkcffbTUbDaz2267LQIAtFqt9M9//rMUAJYvX64bN25cNQCYTCbWs2dPw7fffuv5448/er711lt5I0eOjHnzzTfPXHvttfQk3lWilchJl6dPShkK4N8AJsmdhRAHygLwBoDlOQsmdahtSS61ErncWru6eFlZmcg5h6+v7/nH8BobG5larbbZD+Pm5QyaZWRkuMTGxhqUSiUKCwsVXl5eFo1G0+F++DvbSuRUoEiXpU9KuRbWEacxMkchRE5FABYA+LCjFClnLFDE/pytQNEtPNKlNC18OQXAswASZY5DiDMIArAQwFx9UkoygGU5CybRNh+EtIDmeZAuQ5+UMhpAKoDVoPJEyMUiYN28+LA+KeWWpr9sEEIugwoU6fT0SSnR+qSU1QA2A7DppqOEdEI9AXwLILXpNjch5BLoFh7ptPRJKZ4AngfwCGiPOkLaKh7AL/qklA0AnspZMClD7kCX8+ZtN9j0L0ZPrvypVcsi3HfffWFLly49AwBz584NXrNmjZe3t7dZqVTyFStWnF60aJHf2LFja2644YYaW+a72JkzZxRTp06N2r9/fzYAHD9+XHXnnXd2EwSBd+vWzbB8+fJcQfjreMm0adP0WVlZrq6urhadTmdZvXr1KZ1OJ7U3R2JiYuyAAQPqlixZkt+vX78e48aNq37rrbcKr+JLc2o0AkU6HX1SikKflPI4gBMA/gkqT4RcjQkA0vRJKZ/ok1KC5A7jTJrLU7OnnnqqaN++fdl333136euvv+7viAwlJSXiHXfc0a2hoeH8z/NFixb5ffjhh7m7d+8+VlBQoEpNTb3sQsDvvPNO3v79+7MHDRpU99FHH3lfbZ7MzExN89IMV3suZ0cFinQq+qSUyQAyYJ0U6yNzHEI6CxHWrYyO65NSkvVJKW5yB3IGl1u7qaKiQqHRaCQA2LBhg0dCQkJsjx494vLy8hQNDQ3sxhtv7JaQkBA7efLkbo2NjWzu3LnBjz32WMiFx9XU1AgTJ06MHDRoUOzdd98dfrkMoijyNWvWnNJqtedHjhYvXlzQvGBmRUWFIiAgwNzS11JRUSFqNBqenZ2tmjx5crdbbrlFf8stt+gBoLi4WLzmmmui4+PjY++7776wK53HYrGwzMxMl+DgYCMA5OTkKBMTE2MTEhJiH3vssRAA+OCDD7wffPDB0KqqKiEuLq5nRUVFh+wiHTI0IRfTJ6X00yel/ArgBwCX/J8aIeSquQGYB2uRmiF3GGfzxhtvBA0aNCh2z549bs8+++w5ADh16pRLampq9i233FL2888/e7z99tu+cXFxDampqdndu3dvXLRoke8Vjmvct29f9tmzZ5V79uy55IiOt7e35OPjc8mnJj/++GOv2NjYBr1eb7pc5ieeeCI8Pj4+tr6+XnjwwQfLAeC3337z/Mc//lHy3Xff5QDA888/HzR9+vTy/fv3Z1dXV4vfffedx+XOFxAQYPr55589+vTpUw8Aubm5yhdffLFg06ZNxzds2KADgH/84x/lR48e1Tz44INh//znP4u9vLzafdtQTlSgSIemT0oJ1CelfArgAICxcuchpIsIArBCn5SSok9KiZA7jLNovoW3du3a082l5u677y4DAH9/f7PRaGRZWVmaoUOH1gHA0KFD644cOaK+1HHZ2dnqlJQUz8TExNi8vDyX3NzcNm0rlZWVpVq4cGHgkiVLzlzpuOZbeMuXL89zcXHhADBixIiqcePGnV+pPDs7Wz1y5Mg6AEhMTKzLzMxUX+58/fv3r1++fLnvgAED6gBAoVDwBQsWBN555536urq68yuN3nfffaW//vqr53333VfRlq/LmVCBIh2SPilF1CelzAVwHMB9oD/LhMjhegCZ+qSUJ/VJKS0vw90FXXhrDQB69erVsHPnTi0A7Ny5U9urV6+GSx0XGxvb+PDDD5/du3dv9rx58woiIyNbvchpSUmJOGPGjMilS5fmXG506krc3Nz+lKVHjx6NW7dudQOAPXv2uPXp0+ey++kNGjSoPjs7W9O3b99GAHj99dcDn3322aLly5fnMGZdGcNkMuG9997znzZtWtmCBQscMlfMHuiHDulw9Ekp/QDsBvAmAK3McQjp6txg3RJmrz4phZYJacETTzxReuTIEfWgQYNiT5w44fLoo4+WXe64DRs26AYNGhT70Ucf+bWlQD3//POBRUVFqkcffTQ8MTExNiUl5ar+P/nCCy8Uffvtt97x8fGxOp3OcvPNN1df7thhw4bVxcTENCiVSg4AkyZNqnz00UcjJkyYEK3RaKTTp08rX3zxxYCJEydWLl68uGDlypXeJ0+e7JCbttNWLqTD0CelqGGdf/EUaAkOQpyRBcAiAP+Xs2CS3Tarpa1cuiZn28qFRqBIh6BPShkD4BCAJFB5IsRZibAuHZKpT0qhzblJp0YFiji3ZJ27eZ7Xe3pW9AWA7nLHIYS0SgSAn/RJKd/ok1IC5Q5DiD1QgSLOK1k3HkCGgkkPf6eaT8P1hHQ8twI4ok9KmU1765HOhgoUcT7JOnck6z4EsBFAOAD4suqBTylWbpM3GCGkHTwBLAGwkVYyJ50JFSjiXJJ1gwGkAfj7xZ96RPyhXwhKihyeiRBiC+MApOuTUq6XOwghtkCTcYlzSNYJAP4F4AVc5s8lY/D4zmV+9lDDu/S3WEI6Jj9Y50YtBPCvnAWTWv1o/pXkJ22z6fIJoQtGdonNhMnVoe8okV+yLhjW23X/RQulPoiVJ/xD/GGHQ3IRQuyBAXgCwC59UkqHfjCkM2wmTNqPChSRV7LuRgDpaMM2LE8rVsb5o6LEfqEIIQ4wEMABfVLKPXIHaa/OtJkwaTsqUEQeyTo1knXvAlgLwLctbxUYvL5VzT9pn2CEEAfSAvhcn5TylT4pxV3uMFerI24mTNqPChRxvGRdHIA9AB5p7ykihHNDZoq/7LZdKEKIjO4EcFCflJIgd5Cr0RE3EybtRwWKOFay7jYAewH0vdpTzVN8EeWF6vKrD0UIcQJRAHbok1Ke7kxrRnXEzYRJ61CBIo6RrBORrHsNwP9g3Xz0qomM+61UvXjUFucihDgFJYDXAKzXJ6W06dZ+R9ERNxMml0abCRP7S9Z5w1qcrrXH6Z8y/X3vd5bRifY4NyFENqcB3JizYFLmxZ+gzYS7JtpMmHQtybq+APbBTuUJAF5VfBzmjroqe52fECKLbgB26pNS/iZ3EEIuhQoUsZ9k3QwAu2D9H6HdiEwK+lr138P2vAYhRBYeAH7UJ6U8IXcQQi5GBYrYnnW+0+sAVgBwdcQl+winR1wv7DngiGsRQhxKBPC2PilliT4ppU1PohFiT1SgiG0l69wBpAB4ytGXXqh8198VjXWOvi4hxCFmA9igT0rxkjsIIQAVKGJL1i1ZtgGYIMfllcwS+rnq1VbtYUUI6ZCuAbDHLIFGoojsqEAR20jW9QawG0A/OWMksOyRY4S0Q3JmIITYVffKRktgVYNJ9pXLt2zZ4vrrr7+eX5alsbGRZWZmurz33nveZ8+eFdt6PkmS/vJabW1tq9bEslhouSdHu+LGrYS0SrJuLIBVAHRyR2EM7CPlWx59DR83NMKFNtAkpBOSOIS8svruATqXM/7u6pLk5OR4W54/OTn5iiPZFosFkiTh+PHjLllZWZrhw4fXnzlzRhkbG9vHzc3NEhERYQgICDDfcsst1RMnToz86quvcmfNmhW+dOnSvDFjxsSo1WrJ09PTrNVqpU8++STPz8/PsnDhQh+LxcL69OnT8OGHH/rNmTPnXFxcnGHGjBn6TZs2nd+6au7cucHXX399VWxsrMFgMLDly5d7mUwmZjKZ2KhRo2pHjx5dp9VqaX0iB6ARKHJ1knV3AVgHJyhPzVTMrF+ifHuv3DkIIfbDwVlxVWP4mfL6MEdfe/fu3ZohQ4bEfvTRR/5btmxxHz58eEx6err6uuuuq6ipqUnLyMg4csstt1QDAOecubq6SiqViqtUKh4bG9uwf//+7F9//fXkDz/8cNrPz8+yYcMG7ZYtW9xvvfXWyvfff99Po9FIn376qc+ePXs0er3ekJqaqj5z5sz5AQ+VSsXXrVvn/vnnn3vv27fPLS0tzc3FxYXv2rXLraCgwCa3N++7777z39e5c+cG//TTT7KP+DkbGoEi7Zesew7Ay3LHuJRRwqERg1lW1h4eFyd3FkKI/VTUG/0dfc3hw4c3TJs2rbxv376NmZmZag8PD8vw4cPrly5divr6egYAjDFoNBquUCjOjwZJkoSysjLFhg0btACgUCj4uHHj6saPH18bEhJimjVrVkRaWppWEAQuCAI8PDwkjUbDZ82a1W3RokV5NTU1QlFRkTI9PV1TUVEhrlixwpdzDs45CgoKVDExMQ2xsbGtXrH8SpYuXUp76LWAChRpu2SdCOB9WJ+KcUqMQfxC9aqyj+FTowkKldx5CCGdx1tvveX79ddf+3777bc8Pz9fFRAQYKqtrRUOHTrkdtttt+kPHDigffLJJ4vmzp1b2tDQIIwZMyaGc44lS5b4nD59Wv3000+Hjh8/vnrjxo26w4cPHxFFES+88ELgzJkzy2bMmFEuiiK8vb3Nzz//fMju3buz7733XsXYsWPrfvzxR/eioiJlVlaW2svLyxIWFmYQBAGSJCEsLMx4pXlQvXv37rlhw4bjffv27XXgwIGsmTNnRvz000+nbr31Vn1paamyZ8+eDcuWLctrPj4xMTF279692Rd8zQHz588PDggIMK1Zs+aUQqHAPffcE5aRkeGq0+ksK1euPO3n5/eXAJIk4Z577gnPzMx0VSgU/LvvvjsZHh5uvvi9kyZNig4ICDCWlpYqASAuLq7h008/deoSR7fwSNsk65QAVsKJy1MzNTN1X6RcvEvuHISQzuWJJ54oTU9PP/L444+fffrpp4vS09OPTJ06tXro0KE1H3300ZkBAwbUzZ07txQA1Gq1tHfv3uzU1NTsO+64o2L48OE1QUFBpvnz5xeHhYUZAGDFihW6jRs3eur1emOPHj0MsbGxjQAgCAIOHjyoliSJAcCNN95YM3DgwPrbb7+9IiAgwJSbm+uSk5Pjkpub63L48GFXAJedcB4eHm5Ys2aNR79+/erWrl3r0a9fv/q3337bNy4urnHfvn3ZZ8+eVe7Zs+ey80YHDhxYl5qamu3h4WFZsWKF54oVK3QGg0HYv39/9k033VQxb968wEu9b8WKFTqLxcIOHDhw9J///Gfxzp073S733jfeeKOgqKhItX79+hMZGRlOP4eVRqBI6yXrXAB8B+AGuaO01kQhdVh/diI7jUfHyp2FENI5bNy4Ufvcc8+FVFVVKcxmM1u5cqX3lClTKnQ6nfniYysrK8XExMTYuro64YMPPsj19/c3nT17Vrl3715Nr169GgAgOjraMHPmzBJ3d3dp9uzZETU1NeKcOXOKn3322cLPP//cJyYmpvHi84aFhZkWL16cZzabYbFYWHl5uWg0Gi9boPr371///fffe0+cOLFq1apVXrNmzSrdsGGDx759+7Tbt293r66uFnNzc5WDBw9uuNT7hw4dWgcAAwYMqDtx4oSLxWJBYmJiHQCMGDGibs2aNZ6Xet+RI0fUCQkJdQBw++23V1ksFsybNy/gUu+NjY01+vv7m3Q6ncQ5b9XTh3KiAkVaJ1nnCuAHAOPljtIWjEG5XPWy1NfwidkCkf68E0Ku2oQJE2o//PBDQ1xcXFVNTY0giiK8vLwsHh4efykfCoUCO3fuzJ4wYUJUenq6Jjo62sA5xyuvvBL473//uwgAEhISGlevXi0BgIeHh3nevHmFu3fvdh0/fnzt/fffH7l58+ajF56zrq5OmDdvXohKpZJE0bpaQkFBgcrDw8OSlpbm+vHHH+dfnCM+Pr7+nXfeCVq8ePGZ5557LmzJkiV5OTk5qsTExLo5c+aUrVixQhcZGXnZ+VOpqamu06ZNqz506JDruHHjqtVqNV+9erUngNJt27a59ezZ8y8lDwB69uzZmJKSogOADz74wLvpqcXai9+7d+9ebSu//U6DfqCQlllXF/8JwCi5o7SHGzP0fF25ZMtc08Oj5c5CCLG9mx944i+vqRRCY6SvNlulEP4yKnS13n//fe/w8HBjVFSUobS0VFFWViauXr3a65133vnTnJ2KigqBMcYBgHOOTZs2ebz22msFHh4elmXLlvkNHDjwfOngnCMzM1Pt6uoqlZeXi3v27NHW1taKISEhxt9++00bHx9//lg3Nzfp8OHDRx544IHQ6667rnr69OnVc+fODZ46dWrlqFGj6i+VeejQofVBQUHGHj16GLy9vc0xMTHGJ554onTGjBn6ZcuW+bq7u1u+//77U5f7mnfu3OmekJCg8/HxMd15552VSqUS69at84iPj49tnsd09uxZ8fHHHw9duXJlbvP7br/99qqff/5ZN2jQoFiNRiOtXLnydHBwsPni906aNCn6av6dyIFxTstFkCtI1nkCWA9gsMxJrgrnMFxvfCX/CI+IkjsLIeTqfDw5CAHhkS0epxQFQ6Sf2zEXhWiTJ9Oa1dfXs7NnzypuvvnmqDfffPNMjx49DHfddZf+t99+O3Hy5EnlQw89FL5x48aTy5cv1508edLl+eefP3fNNddE9+3bt97Pz8/8448/ej700EMlb7/9dsCbb7555tprr62bO3ducI8ePRoGDRrU0LNnT8Ptt9+uHzVqVM2cOXNKH3zwwbDJkydXTp06tWbOnDnBkydPrho3blxdQUGBory8XDx27JjLM888E7Zu3brjMTExNv1anUl6erpvv3799HLnaEYFilxess4XwC8ABsgdxRaquSajn+HjOA6BHp4gpANrbYECAKUoGLv5uh1TK0WDnWNdkslkglL5x9JMGRkZLrGxsQalUonCwkKFl5eXRaPR/OUHscViQfPtuZaUlZWJnHP4+vp26uXIna1A0Q8ScmnJugAAm9FJyhMAeLCG3i8oPt8mdw5CiOOYLJLqVEldbIPRopbj+heWJwDo3bu3ofm14OBg86XKE4BWlycA8PHxsXT28uSMqECRv0rW+QD4DUAvuaPY2l3ipoRIVpjb8pGEkM7CLEnKU6W1sXUGs9M/Gk86DipQ5M+SdR4ANgDolCt4MwbX71TzKwC6d01IV2KRuCKnrC62wWiWZSSKdD5UoMgfrEsVpACw6caczsab1fR/VrFiu9w5CCGOZZG4eLq0PsZgtnT63Qn27dunXr9+vdZstvlDiKQJLWNArJJ1KgCrAIyQO4ojzBZ/6v+VZXzBGe4fIncWQsjVKTnWpr/zKYuOos+VDhg39uT+K31+2rRp+tmzZ5dOmDCh9plnngkKDQ01fvXVV74rVqw4FRUVZbrw88uWLfN89913/ffs2XMsIyPD5bHHHgu79957S7/++mufm2++uSI7O1u9fft2d6PRyFQqFQeA5i1UFi1a5JOfn6967bXXii6XJSQkpE9ISIixsbGRDR8+vOaDDz4oePvtt31/+eUXDz8/P/OSJUt8V69enXP06FHVLbfcEqVWq6V33nnnzIgRIy653AFpPSpQpHlvuxUAJsgdxVEYg/v3quTsRMP7VKAIIXazfv16j0OHDrlVVVUJUVFRxpKSEuWxY8fU+fn5qoKCAqVerzds377d/fvvvz8ZFRVlauv5RVHkzYVr2LBhMenp6S4lJSWKH3/88ZRCoUBMTEwcADz88MPhCxYsyB85cmTdtGnTum3atOmkrb/WroZu4XV1yToG4DMAN8sdxdH8WeWgx8VVdCuPEGI3e/fudZ86dWr5Tz/95K7RaLgkSTh58qSLv7+/KT8/X9WtWzebrNtkMplQX18vaDQa/t///re4qqpKfOGFF/xHjBhRAwAnTpxQ33DDDTVN26TAZGpzVyMXoQJF3gVwt9wh5PKE4rvegSg/K3cOQkjH8sQTT4QnJibGLl++3Pdyxxw6dMglKCjIOHny5Mr169frAECj0UhlZWWKyMhIw6FDh1y7d+9uAIBp06ZFJSYmxt5zzz1hbclhsVhYYmJi7JAhQ2JnzJhR1ryQZnZ2tmrdunWeer3eAAAeHh7nlzlwdXWVioqK6A7UVaJvYFeWrJsP4GG5Y8hJYPD8ziV5zwjDogC5sxBCOo533nknr3kOFAA0b9nSjDHG165dq8vJyXF54403AsvKypQAEBwcbCwsLFRdc8011cuWLfPr1q2bCQBscQvvQsOGDWvYvn37sejo6F7PP//8Ocb+2Ju3rq5OlCTJ6TfrdXY0AtVVJevuBfC83DGcQSgrHXy/+PMuuXMQQjouPz8/87Fjx1wAIDc31yUkJMS8adMmj6+//vrU/v37s318fEwZGRku4eHhxtDQUGN0dLTBx8fH5OLiYvMlVeLj42NLSkrEhoaG8xPTPTw8zHl5eQpJkpCXl+cSFBREj+ddJRqB6oqSddcA+EjuGM7k34rlMWssw8vKoPOROwshpOP517/+VfyPf/wj4tlnn+UDBgyoi4yMNB49etR16NCh9QAwatSomrVr13pEREQYVSoV79GjhyE4OPj8/Kdp06ZFNZedjz/+OKdfv37t3nrmmWeeKR4zZkyMWq2WkpOTCwDgH//4R8nkyZOjQ0NDjcOGDauxR3HramgvvK4mWdcTwE4AnjIncTonpaBd44xvDpU7ByHkytqyF15bMAChXq4nvdxUlTY/uRPYtWuX5tSpU6oZM2ZUtWWrGGdBe+ER+STr/GFdKNNT5iROKUooGnq7+OseuXMQQuTBAeRXNkRWN5jc5c5iD0OHDm248847O2R5ckZUoLqKZJ0GwFoA3eSO4sxeUizVe6C2Su4chBB5cM7ZmYr6qEZT51+tnFwdKlBdgXWtp2UABssdxdmJjAesUL18WO4chBD5WCQu5pbVR1skTj8jyWXRH46uYQGAaXKH6Ch6CbkjbhR27pM7ByFEPgazRXOmvD5C7hzEeVGB6uySdXcCeEbuGB3N28r3g9zQUCN3DkKIfKobTd7F1Y2XXSNOkqS/vFZbW9vi+koWi6WlQ0gHQMsYdGbJur6g5QraRcGkkGWqV7bdbHxhpNxZCCHyKaluDNUoxXqdRvmnv1AtXLjQx2KxsD59+jR8+OGHfnPmzDkXFxdnmDFjhr55n7m5c+cGX3/99VWxsbEGg8HAli9f7mUymZjJZGKjRo2qHT16dJ1Wq+W//vqr29dff+398ssvF06bNi1y5syZZZ9//rlvfHx83YoVK3zLysrSAWDv3r2aiooKEQCWLFni27Nnz8ZRo0bVAoC3t7c5ISGh0dHfn66MClRnlazzBLAKgKvMSTqsAezEiGuFfWkbpUH95c5CCLm8647n2PR8v3TXn/81B5BfUR+pVmiPuChFIwBs2LBBu2XLFveFCxfmP/7446Fubm7Sp59+6jN9+vQKvV5vSE1NVQcGBpoBQKVS8XXr1rnn5eWp0tPTXTnnbODAgXW7du1yi46ONvr6+lqqqqpEURR5VVWVGBgYaPr73/9e/r///c/73XffLcjMzNQ0Z6mtrRWqqqoEQRBgsViY2WxGTU2NIEkSlEolPVrnYFSgOiPrpPGvAETJHaUjYwzsfeVCr76GT+ob4EJFlJAuyiJxRW5ZfVS0v/aoIDA+fvz42pCQENOsWbMi0tLStIIgcEEQ4OHhIWk0Gj5r1qxuixYtyisqKlKmp6drKioqxBUrVvhyzsE5R0FBgSomJqYhNjbWuGzZMs/333/f/+zZs8qhQ4fWbdmyRffee+95A8BDDz0UmpWV5QpYS9vf//53vb+/vwkADAYDy8/PV/3+++86ACgsLFT98MMPx+Pj42kUykGoQHVO/wdgktwhOgMls0R8onxjy52mf4+WOwshRD6NZotrXkV9hN7HLUcURbzwwguBM2fOLJsxY0a5KIrw9vY2P//88yG7d+/OvvfeexV1dXVCUVGRMisrS+3l5WUJCwszCIIASZIQFhZmbJ4Hdffdd1dGREQY16xZ45mQkFCv1+sbGWMoLi5W3XrrreXbtm1zBwCTycSuv/76infffbfgpZde8i8oKFC9++67+WvXrvWYMmVK9cMPPxwqCDSt2ZGoQHU2ybq/AZgnd4zOZJiQOXK4kJGxQ+rdW+4shBD5VDeYfM5WN9b/lrLasHHjRs9HH320RBAECILAS0pKFIIg4ODBg2pJktiNN95Y8/vvv7tPnTq18uDBg5rc3FwXxhg456isrFTExcU1AMCBAwfUn376qc+ePXvcx4wZU/Pss88WiaLIVSqVFBwcbPrvf/+bDwBjxoyp7dWrV+O9994bDlhv5z322GOhOp3OrNVqpY8++ihfzu9NV0QFqjNJ1kUCWA56utKmGIOwVPm6po/hE4MRShe58xBC5HOu2hAaoo/MmTlzZom7u7s0e/bsiJqaGnHOnDnFzz77bOHnn3/uExMT86fbaGFhYabFixfnmc1mWCwWVl5eLhqNRgYAOTk5Kr1eb/Tx8akcPnx4fXx8fE9BELivr6/5qaeeCu/Xr1/dlClTarRaLV+7dq1rTU2NsH37do/w8HDDmTNnXGpra8VFixYFffzxx6fvuuuuSlm+KV0UFajOIlmnBvA9AC+5o3RGLswU9b5y4ZYHTE/RrTxCujAOznwieoRpXN1KAcDDw8M8b968wt27d7uOHz++9v7774/cvHnz0ebj6+rqhHnz5oWoVCqpeQuVgoIClYeHhyUtLc31448/zvf19TWvWbPG08fHx7J27drjTzzxRNiGDRtOTJw4Merll18ubD6Xr6+vOTg42PTVV1+d+uGHH3Th4eHGCRMm1BQUFCgNBkOLyycQ26KRis7jDQD95Q7RmY0TDgwfxLKPyJ2DECIvi8QVjVz0zsjIULu6ukrl5eXinj17tO+9955vSEiI8bffftM2H+vm5iYdPnz4yIABA+qeeuqpor1792bfdtttZUuWLMn5+OOP8wGAc37+3H379jXExsY2xMXF9br11lsrevToYQSAqqoq4bvvvvPKy8tT9e3bt9HNzU3S6XQWV1dX6aWXXgraunWr1mQyOfx70ZXRCFRnkKybBOARuWN0doxB8aXqFaGv4ROTGQql3HkIIVYXLjvgKAajSVVRa/CeP39+Yc+ePQ2rVq3yCg8PN2ZmZmY9+OCDYWvWrHG3WCwwmUwMAObPn19cXl4ufv/99x4//PCD10MPPVQKALm5ucrZs2fr582bV/Dxxx97ffHFF76enp6W+++//9xXX33l8+WXX/rOmTPn7JgxY2pHjhxZe/fdd1euXbvW/ejRo+oHH3ywLCYmxrhjx45j33zzjU6ppP8tORK7sPmSDihZFwDgEAB/uaN0FWstQzc/bnpsjNw5COmqPp4chIDwSLljgIHxSD+3o24uinqLxYLmW3RXUlZWJnLO4evr+5flyMvLywW1Ws1dXV3P/2Curq4WFArFn17rqtLT03379eunlztHM7qF1/F9BipPDnWjsGtYL3b6hNw5CCHy4uDsTEV9N0nirDXlCQB8fHwslypPAODt7S1dXJQ8PDz+8hpxDlSgOrJk3WMA/iZ3jK6GMaj+p3rJIECiDa0IkQEHh7PcPTGaJXVBZUOo3Dk6O0mSGIC/bj4oIypQHVWyrjeA1+SO0VW5s4Ze/1V8ul3uHIR0RbmVJpjrq52mRFXUG/2rGkzucuforCRJYiUlJToAGXJnuRDNgeqIknUuAFIB9JE7SlfGORonGF8tOsbDusmdhZCuxMNFwGODvRDhqQSDczy9LzJYvDViIWPONUrSSUgAMsxm8wPx8fHn5A7TjApUR5SsexvAE3LHIEAldzvU3/BRH4A5x//FCSFyWp6zYNJdcocgjkG38DqaZN1oAHPkjkGsPFld3+cVy7bJnYMQ4hTu1Cel3Cp3COIYNALVkVhXGz8EoLvcUcgfOEfdGONbFbk8kCaSEkLKAfTOWTCpSO4gxL5oBKpjmQcqT06HMbh9r0p2mvvyhBBZeQNYKncIYn9UoDqKZN0AAE/JHYNcmi+rHjhX8Q09lUcIAYCJ+qSUh+QOQeyLbuF1BMk6BYC9AAbIHYVcHueoGm5YVF8I3yC5sxBCZFcH6628HLmDEPugEaiO4UlQeXJ6jEH3vUtyvtw5CCFOwQ3AYrlDEPuhAuXsknXdASTLHYO0ThArT3hIXLtT7hyEEKdwgz4pZarcIYh90C08Z5asYwB+BzBa7iik9STOyhMN71lK4ekndxZCiOzyAMTlLJhUJ3cQYls0AuXc7gOVpw5HYNz7O9X8k3LnIIQ4hXAAz8sdgtgeFShnlazTAXhF7hikffTC2SF3i7/sljsHIcQp/FOflNJL7hDEtqhAOa95AOgWUAeWrPgiyhM1FXLnIITITgngfblDENuiAuWMknU9ADwqdwxydUTG/VaqXsySOwchxCmM0ielzJA7BLEdKlDO6R1Y/8ZCOrhYIX/4NGFrqtw5CCFO4TV9Uoqr3CGIbVCBcjbJuhsBTJA7BrGd15QfhbqjrkruHIQQ2YUB+JfcIYhtUIFyJsk6FYC35I5BbEtkUtBXqlcOyZ2DEOIUntYnpUTIHYJcPSpQzuUJANFyhyC21084NXKisOeA3DkIIbLTAHhD7hDk6tFCms4iWRcI4BgAd7mjEPswcfFMP8PH3vVQu8mdhRAiu2tyFkzaLHcI0n40AuU85oPKU6emZJawz1Sv7Zc7ByHEKbwmdwBydahAOYNkXTSsq46TTi6RHR05Rkij+VCEkAR9UsqNcocg7UcFyjkkA1DIHYLYH2NgHynfcneBsVHuLIQQ2c3XJ6UwuUOQ9qECJbdkXW8At8sdgziOipm7LVG+tUfuHIQQ2Q0AMFXuEKR9qEDJ70XQv4cuZ7RwaEQiO0KrlBNCaBSqg6If3HJK1iWA/vbRJTEG8UvVAqUSZqPcWQghsuoD4Fa5Q5C2owIlr5flDkDko2am7guV7+6SOwchRHbz9Ekp9PO4g6F/YXJJ1o0BcK3cMYi8/ibsHdaPnTgmdw5CiKziANBGwx0MFSj50OgTAWNQfq162SLCYpY7CyFEVs/rk1JEuUOQ1qMCJYdk3TgAw+SOQZyDGzP0fE350Q65cxBCZBUL4E65Q5DWowIlD9qNm/zJzcK2IT1Y3im5cxBCZPW8PimF1gTsIKhAOVqybgBo7hO5CGNw+Ub1Qh2DJMmdhRAimygA98gdgrQOFSjHe0buAMQ5ebD6PsmKL7bLnYMQIqv/6JNSlHKHIC2jAuVIybpI0Hof5ApmihsHdWOFeXLnIITIRg96Iq9DoALlWE8CoKcsyGUxBtfvVPPLAM7lzkIIkc1jcgcgLaMC5SjJOj8As+SOQZyfD6sZ8C/F/+hWHiFdV4I+KWWw3CHIlVGBcpzHAGjkDkE6hofEH/uHspJCuXMQQmRDo1BOjnG6U2B/yTo3AHkAvOWOQjqOs9xz32DD+4PkzkEIkYURQHjOgkln5Q5CLo1GoBzjHlB5Im0UwCoHPSqupgU2CemaVAAekjsEuTwqUI7xD7kDkI5pruLbXgEoPyd3DkKILP5OSxo4LypQ9pasGwGgt9wxSMckMHh+p0o+LXcOQogsggDcIncIcmlUoOyPRp/IVQkTSgffJ67bJXcOQogsaDK5k6JJ5PaUrPMFkA/ARe4opGOTOCsdZHiflUPnI3cWQojDDcpZMGm/3CHIn9EIlH3dBypPxAYExn2/Ub2QLXcOQogsaBTKCVGBspdkHQMwW+4YpPOIFoqGTRd/3yt3DkKIw83QJ6X4yR2C/BkVKPu5DtadtQmxmVcUn4R7oLZK7hyEEIdyAf2F3OlQgbIfWr+D2JzIeOAK1cuH5c5BCHG4h/RJKfQz24nQvwx7SNYFA7hR7hikc+ol5I64QdhFE0oJ6VpCAYyWOwT5AxUo+7gdgCh3CNJ5vaN8L9ANDTVy5yCEONTtcgcgf6ACZR93yh2AdG4KJoV8qVpwUO4chBCHmkYrkzsPKlC2lqzrAWCA3DFI5zeQHR85TtifJncOQojDeAOYKHcIYkUFyvZo9Ik4BGNgHyjf8VLD0CB3FkKIw9BtPCdBBcr27pA7AOk6VMwS8bHyTVobipCuY7I+KcVV7hCECpRtJeuGAoiUOwbpWkYIGSOHCRmZcucghDiEG4ApcocgVKBsjW7fEYdjDMJS5etqFUwGubMQQhyCbuM5ASpQtpKsUwCYLncM0jWpmSnqPeWi3XLnIIQ4xAR9UoqX3CG6OipQtnMdANqriMhmvLB/+EB27KjcOQghdqcCcIvcIbo6KlC2Q3+YiawYg+Ir1StMhMUsdxZCiN3RbTyZUYGyhWSdAOAGuWMQ4soMsW8qP9ghdw5CiN2N1ielBMsdoiujAmUbQ0C374iTmCLsHBrHck7KnYMQYlcCgNvkDtGVUYGyjclyByCkGWNQrVS92ChAssidhRBiVzR1REatLlCMMXaJ1zSteJ9w0e/1jLGerb3uBe8TL/i1cPF5ZXaj3AEIuZA7a+j1kmLpdrlzEELsarA+KUUnd4iuStGagxhjswCIjLEsALMBvAvgBIDPAUxtOiYZwAYAp/DHEwJKAErG2HYAeznnDQA8ASwEMJoxtgRALwCNTccWcc5nNJ1vJIBwABoAPwL4gjEWAIADKAbwDoBfmo7dCsDU9LlmYZzz2LZ9O9ohWRcFIM7u1yGkjW4Xf0v8zDIx5zgP1cudhRBiFyKAcQBWyR2kK2qxQDHGRgAYA+AZAK8DqAVwD4DvAJxijPUGUNJ0uAnANbAWn/6wjnDtAzAYQC5j7AyAQwD+c8HxdwGobMry5gWX/j8AHzVdN55zPpEx9jiAg5zzbRfFNAGYwDk///QRY2xLi1+9bdDoE3FKjEHzrWp+VX/DRxz46wgyIaRTmAAqULJozQjUTlhHfJbAOlnaAkACUA2gAcBnAB4FEAzraJIXgHsBsKaPcABZnPMcxthUAI8DCGWMvXPBNXYDGIk/jyCZmv75Nuf8c8bYHAB/A9CTMXY/gP9wzvMv+Dq+YIxd+H5HTeqm+U/EaXmyun7/USzf+pL5rlFyZyGE2MV1cgfoqlosUJxziTH2LIAvAHwNa3mqAPAygNEAAgC4AgiB9VZWBYDTTccJAHJgHWYE53wNYywFwK8A/gfghabLFOCC8sQYuxOAN6xlizXdQjwB4CEA9QCeA6BumgfFAExsvsYFpOZ5UpxzqbXfkDZJ1nnCWvwIcVr3iz8P/NJybX4eDwiVOwshxOb0+qSUmJwFk47JHaSrac0tvBtgHWX5ANZSJAHwafpnTwAC5/x3xthoAD8B6AMgCtZCxGAtQoeazqUC8GXTqYc2Xd8Ff0xmVwEA53w5Y0yLP0ahTgCYCetGvfcCKG96/VoATwIwAhgO4OL1b0RYR8i+aenrbKeJaOU8MkLkwhi036uSsxMMH1CBIqRzug4AFSgHa80P/xwAH8I692kJAB2sc6FehHX+UvZFxxfAOlKkgLXAeKKpGAF4BIAWQC4APYA3APgDqAMQCOvIEhhj3rDuNr0U1lGtG2Ad2XIBUAhADQCc8w0ANjDGwgEs4Jzf0eqv3DYmOPh6hLSLH6uK/6fi2+1vm28dIXcWQojNTYD14S7iQC0uBcA5z4C14ADWyd5PwHq7LhPAA7A+IdfMFcBLTR//AfAsgFcBzGWMvQlgMawjSBbO+Xuc8xMAbgKwC9ZCldd0HhHAP5t+/RCAf8M6CtUbQBaAIljnYjXrDiCYMbb5go8axphba74JV2Gsnc9PiM08Lq7uE4SyYrlzEEJsbow+KUUpd4iuprVrKTEAsbAWKS9Yb789AOvo1IVzgOo554kA9gJ4lXM+BtalDh7knD954VNyAMAYuxbWYnS2KcsgxtirsN6iiwYwB8AdnPMjsD71dwOAUlhHtc40n4dz/ivnfEzzB5qGMznndbCXZF00rBPkCekQGIPuO5fkvJaPJIR0MFpYp7EQB2ptgXKBdT2mFwH8DOvtvDwAA2F9Km48rKNGzbcEFwA4wRibAGA6/ljmoPlcCsbYjQAGcM6XADgO623BL2F96i8R1iHJ6ZzzzYyxYQDeBzCTc/4zrMXt7xeHZIyFMcaOAtgD4KtWfm3tNc7O5yfE5kJYWeLfxR93yp2DEGJzNKXEwRjnvOWjLn4TY0JrnmxjjOmarlHZjmztwhgTOef238IiWfcNgFvtfh1CbEzirDzR8J6lFJ60fyMhnceBnAWT4uUO0ZW0azuU1i4LwDmvcmR5arqmo/b/Gu2g6xBiUwLj3t+qXjghdw5CiE0N0Cel0F+KHMiZ9pPrOJJ1PWB9epCQDqmbUDz0LnHjbrlzEEJshsG6tA9xECpQ7UOjT6TDm6/4PNITNRVy5yCE2Aw9Ge5AVKDah7bFIB2eyLj//1QvZcmdgxBiMwlyB+hKqEC1DxUo0in0EM4Mv0nYlip3DkKITfTSJ6Vo5A7RVVCBaqtkXTAA2hKDdBqvK5eEalFfLXcOQshVEwEMkDtEV0EFqu0GyR2AEFtSMCnoK9Ur6XLnIITYBP2MchAqUG1HfzhJp9OPnRwxQdh7UO4chJCrRvOgHIQKVNtRgSKdDmNg7yoX+7ii0X7bHxFCHIF+RjkIFai2oz+cpFNSMkv4UtXr++XOQQi5KrH6pBR3uUN0BVSg2iJZFwGAVnolndZgdmTEKCH9kNw5CCHtxgDQli4OQAWqbWj0iXRqjEH4WPmmuwuMjXJnIYS0G82DcgAqUG1DBYp0ei7M3O0D5Tu0zQshHRf9rHIAKlBtQ38oSZdwjZA2MpEdoVXKCemYaATKAahAtc1AuQMQ4giMQfxC9apSAbNJ7iyEkDbrpk9K8ZY7RGdHBaq1knWBAOgPJOkyNMzYfaHyvZ1y5yCEtAvdMbEzKlCt10PuAIQ42vXCnmF92cnjcucghLQZPYlnZ1SgWo8KFOlyGINyheplswDJIncWQkibxMgdoLOjAtV6sXIHIEQObqyx56uKj7bLnYMQ0iaRcgfo7KhAtR6NQJEu6xZx6+BYlnda7hyEkFaLkjtAZ0cFqvWoQJEuizGov1G9UMsgSXJnIYS0SrA+KUUtd4jOjApUayTrNADC5Y5BiJx0rL7PPMWXdCuPkI6BAegmd4jOjApU63QHfa8IwT3iL4O6scI8uXMQQlqFbuPZEZWC1qHbd4QAYAyu36nmlwGcy52FENIiKlB2RAWqdehxUEKa+LCaAc8oVtKtPEKcHz2JZ0dUoFonQu4AhDiTf4hr+4WykkK5cxBCrohGoOyIClTrhModgBBnwhg8vlMlU4EixLlRgbIjKlCtEyJ3AEKcTSCrGPSIuGaH3DkIIZel1yelMLlDdFZUoFqHRqAIuYQnFd/0CkD5OblzEEIuSQ0aALAbKlAtSda5AvCSOwYhzkhg8PxWNf+U3DkIIZdFt/HshApUy2j0iZArCBdKhtwrrt8ldw5CyCXRk3h2QgWqZTT8SUgLnlcsi/ZGVZncOQghf0E/w+yEClTLaASKkBYIjPutVL14VO4chJC/oCkodkIFqmVUoAhphe5C4fBbxc175c5BCPkTb7kDdFZUoFoWLHcAQjqKBYqPw91RVyV3DkLIeTQCZSdUoFrmI3cAQjoKkfHAFaqXD8udgxByHhUoO6EC1TJPuQMQ0pH0FnJGTBJ275c7ByEEAN3CsxsqUC3TyR2AkI5mofLdADc01MqdgxBCI1D2QgWqZZ5yByCko1EwKfQL1asH5M5BCKECZS9UoFpGI1CEtEM8OzZyrHAgXe4chHRxrvqkFBe5Q3RGVKBa5il3AEI6IsbAPlS+o1PD0CB3FkK6OBqFsgMqUFeSrFMAcJM7BiEdlYqZ9R8p36K1oQiRFxUoO6ACdWV0+46QqzRSODxymJCRKXcOQrowehLPDqhAXZmn3AEI6egYg7BU+bpaCbNR7iyEdFE0AmUHVKCujEagCLEBNTNFvatcuEvuHIR0UVSg7IAK1JXRkwuE2Mh1wv7hA9mxbLlzENIFUYGyAypQV6aQOwAhnQVjUHylegUiLGa5sxDSxSjlDtAZUYG6MipQhNiQKzPEvqH8cIfcOQjpYkS5A3RGVKCujAoUITY2VdgxJI7lnJQ7ByFdCBUoO6ACdWX0h44QG2MMLitVLzYySJLcWQjpIuhnmR1QgboyGoEixA7cWUOvlxRLt8mdg5AuggqUHVCBujIqUITYyR3ib4lRrCBX7hyEdAFUoOyACtSVUYEixE4Yg+Y71fxKgHO5sxDSyVGBsgMqCFdGf+gIsZNspfLU2wptaRJPW5ExwKI94+GrPcFitOXwieBMCJA7HyGEXAkVqCujAkWIjRWLYvETAb7HM1WqYY/9KOVZtF7Bt9a6Gff5ZrvdEf1tg4/PGUU5fM4eRr/cNMTXH0eMtgqees4EX7mzE9JB0QMbdkAF6soscgcgpLOoFljVc34+aVs0mgQwNhKc86FHeLcdw/Q1aUX/q52suNt1Y4afIVtR7hoefmjfqNDNIWOE3yKb33+WBxQcQv8zaRjYeArRumroIsEYbbdESMuoQNkBFagra5Q7ACEdnREwvubjtesbd20fztjo5tcHnuCHFBL6iRbjfqYZ4fJrwRfeN4bODjxsOXNg72nFgJycAW7+/qf3dYvcL6hUjQMDcDbkWmwIuRYbAAAc4IU8JC8dA/PTMcCUg0jPWmijwJhWti+WEOdEBcoOqEBdGRUoQtpJAqSlOo9d73rpIiwXFKdmM7ZKtQAgWgwm0bX7kLq6DZlbz35nGRVwa0KI5J2/VrVPOncuctC5c5HQupce69599zk3t4pExqACAAawEBSEh6Ag/Hr82HRNJp3hEafSMLDoEPpb8qD3rodrFBjTOPSLJ8S5UIGyAypQV0YFipB2SHFz3Z/s661tFIThl/q82shrI86hPwCIlkYzAChcR9UW128anFm5Y1tvrxEj7zKMql+rSt1RIdQNr63xjTl44IYYlar+XFT03iwfnzN9GIPPxecVwIUI5ERGICdyClYBACQIltM88ngaBhYfQn/kI9ynEepoMKay33eAEKdC01HsgArUlVGBIqQN9qldsub6+xoqRDH+SsdN3i2lMWAEACjNDRYAEFV9Es31v5/MrNwx0k8dtjVAEzFqmnHI8H2Kk9vSxJwEMKiNRlf/I1lj/JlgbgwPP7wtNDQrWBCkqCtdS4AkRuFE9yic6D4N3wAAzFAYT/DuR9Mw8FwG+gkFCPE3wiUSjNH/E0lnVCt3gM6I/mdxZVSgCGmFU0pF7uMBfoW5CsUQMMZaOn7iPu7R/GuFqR4AwBhjCvXgInPjzqgtxSuH3xj28H6NQhs/yBw1Mtzim/2Tar9aYjwCALikUOfmDBiZm9Of+/mf3hfZNE+qtXkVMKt64EiPHjjSA1gOADBC2XiM9zh6EIPKM9FbLEZwoAnKbmCM1ssjHV2N3AE6IypQV9YgdwBCnFmpKJT809/vSJqLaigYi2jNe0JL+GmtAX2bf680153/nKhOGGxu3FXAwUPWFXwSPSX80dMiU3Tz57rYuwyjqler9u6uERqG/HE2xkrORQ4qORcJrbb0ePeY3Wfd3CoSGINLW78WFUzq3jjcuzcOn3+tAeraozzu5EEMqjyCXspzCAg2QxHRmpJIiBOhAmUHVKCujEagCLmEOsZq/8/PZ99GV80gMDaqLe+9c7OUB6Bb8++VprrzIzyMiUrRpf8Ji+FgiEky6DYWfFE+IeS+KsaYTgWFx23GYUN2KrK3Zon5Q8GgvPC8tbW+3Q8euKG7UlVfEhWVmuXrm9eLMVzV2lEaNGoH4EC/AThw/rU6uFVl8j6nDiK+Ohs9XUrhF2phitCruQ4hdkYFyg4Yp10ULi9Z5w/grNwxCHEWJsD0trfnrq883Htyxvza+n5B4pblr1lKRI7A5tfyQsfuOhE9bWjz7zk3NRgqF9cB1vIT7ha3b4jfDQMYY+cXti0UyjPXKdM8OeMhl7sWE8yN4WEZqaFhmS3Ok7pa1fAoO4y+OWmIrz2GHppy+IRLTAxs+Z2EOMTw4mv675Q7RGdDI1BXRrfwCIF1zaWvPNx3veXtGWJu44jThYZn8oMix6ALX1Oaav80ksSYUiOoeuyRjEfHAEBeXdYgP3XolmiPAeeXQgiWvHvdaRhRscplb2o9MyRcMrOkUOfm9h+Zm9uP+/nl7I+M2geVqvGKk9vbywPVPsOx3Wc4tp9/rYJ7nTuE/jlpiG84jhjXSnjpORPaXDoJsQEagbIDGoG6kmSdAMAI2tKFdGGbXDUH/+3n41IvCHFXe65FH5h3BVZi6IWvlXnHHU7v+0ifC1/jUmOVoep9AYB782vXBd+73cslYMSfjgPnW5RZW04IxSPBWv7vVKstO969++6zbtryds2Tulol8CtMx4Dm1dTdq+DZDYx5OToH6XK6FV/TP0fuEJ0NFaiWJOtKgKubR0FIR5Tuosp+wt+vtlRx5SUJWsu9npd/stCiZcCf1l+qdo84vi/+me4XH2+sWbVFMuecH3USIBinhD+WrRLVfS4+NlcoSdukPBTMGfxbk0WpbCiJik7N8vXNjWMMso4KFSE4Lw0DCtIxwJiDKF0N3CPBmEfL7ySk1XyLr+lfJneIzoYKVEuSdUcA9JA7BiGOkqdQ5D8e4Jt3UqkcasunzWb9Ytnyt/38LyuS16t9C3YPmf+XuUxcqjlrqPrYE/hjpEgtupXcGPawSWBC8F/OA0PJKpc9+Y3MNKC1mZrnSYWEZgWJoiW69V+N/XCAn0FEThoGFB3CAHMe9F51cIsCY65yZyMdlkvxNf2NcofobKhAtSRZtw1NC/4R0plVCEL5U/6+h/eqXYbaY5XuL98wZ6tNiL34dZPCrXLbiNc8L/UeQ/XXW7ml+E9zrnxcQo6OC7oznF2iUEjgll+Vh7flCiWjwdCm8ufnd3p/ZOR+rnJpGNTy0Y4lQbDkoNupNAw8exj9pTMI92mAJhqMOfw2JOlwTMXX9KdV9+2AClRLknWrAUyVOwYh9tLAWP18X+/UFDfXAfa6dRSTz7NfWmb5S3kCAIkJ5s2jF1/ygRbJUp5nrP48BBfNQ+zuMXDXAO/xQ9hlRshOCMX7NiszI8Hg3dasbtqyE9277y7SWudJqdv6fkcxQzSdRPeTaRhYkoG+KECYnwEuUWBM2fK7SRdSWnxNf3p4wQ7oKbyWlcodgBB7sACWd710O5fqPGKkS2z2a0t3bLYUA38dfQIAgUsKcN4Ixv5SVgTRO5wJ3ju5VD7swtePVx8Y6qcO3xLmFnvJ3NFS4KAAo65wtWrvYSMz/2XO1JXU1fpEpx2cFK1UNpRGRafucYZ5UpeigEUZi6M9YnG0x234GoB1NfXjPPbYQcSXZaKPUITgABNUkbhgCQjS5dBSPHZCBaplVKBIp7PSXbvnVR8vfxNjI+19LYWZG3qe+WPl8UvjtcBfCxQAKN0m+BprVvzl9Z3n1oyaFPr33Vql55BLvA3uXBN8l2Gk33pl2pZCsaLNBdFk0vgePTJqNGMWQ1h4xrbQ0MxAUbT8ZbK7M1HBpO6FjF69kHH+tUa41B3lcafSEF+RhV6KswgKMkOhp9XUu4xiuQN0VlSgWkYFinQaWzXq9H/5+4q1gjDYUdccn8YPMPx56YKLMS7VcSZc8mlXQREUA6ZNBa+9eL0ntr5gaZ+p4Y9lKwTlpUe3ICivNw0cfUTK371Dkd0TDLq25udcdMnL7TcyL7cffP1yDkRG7pNUqoZ41sY5VnJRw+DWHwf79MfB86/Vw7U6i/c+dRDxVUcRpyqBf6iFKcJkjEnsx+4jUIwxxi+aD8QY03DOr7iWImNM4JxL9k1nP1SgWkaPfpIOL0ulPDEnwK+iWKG45KKT9jR1l9TinBxBMjdYhMv/70jpdq3aVLv6L69buMltfcFSt0mhs0sZY5ddbqSnJXRIkOSVu0a1t8jMpHY/VVtaoh9YWqKHm1v5ye4xuwu12jKnnid1Oa6o9xiEvf0HYe/512q4e0UG+p5Ow8CabPRUl8E3TGLiX552JB2OXUegGGOzAIiMsSwAswG8C+AEgM/RNH+YMZYMYAOAU7AuY3ILACUAJWNsO4C9nPMGxtgQALcBeAnACgCfAXgAwB4A93POA5rO1wc4/5ehBwFkAdjR9PtKzvkfQ7B2RAWqZSVyByCkvQoUYuEcf79T2SrlMDAmtPwO2/Kp4kVetRjY0nGCZG60XOHzorJbHxNzOQRu+MutwDpzZei2s9+ljwy4RceuMIHak7tF3GUY1ZiiOrCtRKi+qluXdXXeUWkHr49SKhtKo6JS9/j6Oec8qbZwR43XUOzwGnr+5xBQwT1LMtAv5yDi648jVlMB7260mnqHY7cCxRgbAWAMgGcAvA6gFsA9AL4DcIox1ht//Aw1AbgGQDiA/gAEAPsADAaQyxirAOABwALrArqFnPMVjLE7OefPMcYu/G/ftekYDusDJgoAWgCs6ToOQQWqZQVyByCkraoEofJffj7pOzTqwWBMtlGEGVulYwwIauk4QTIYrf//uzyl5hqDqX79JT9X1HCqX1blrm29vIZdsRgpIKqnGBNGpou5O1IVJ/qDwa2lbFdiMml8jx4dNZplWwxhYRnbQ8MyA5x9nlRbeKHSbyS2+I3ElvOvlXLf4kPon5eGgQ0nEeNWBV0kZ0Kbn3YkDlNox3PvhLWgLQEwBNbyIwGohnUrtM8APAogGEAvAF4A7oW16DBYy1QW5zyHMTYVwGNNx+4GMJExdjcAMMZeg7V0NZe2TwEUNWVQA9ADuLbp9+GMsRs451n2+ZL/QAWqZTlyByCktQwMjS/7eO9Zo3Xrx+38ZF1rDMviEa05TmExmAwtHCO6xCWY6jdlA+ZLznfKqNw20k8dusVfE97i193PEjE8VPI+uVa1DxZ29RsNcy665OX1G5GX1w++vjkHIqM61jyptvBFaeBYbAoci03nXyvmQfnp6J+fjoGNpxDlWQOPbmCszfPNiF3k2+vEnHOJMfYsgC8AfA1reaoA8DKA0QACYB0tCgEQ1/S5003HCbD+fBWbzrWGMZYP4AYAaQCOwTrCFALgfwDGNV1WAWA1gGcBzGn6/LNNn98E4NWm89sdFaiWJFdVIllXBbR98ikhjiIB0hJPj51LPHWRFicoTgDQ/6R0SCm19PSdlcLccKU7eH8cpxleZm7YctnPby7+34gbwx7Zr1G4tbj9jA93j7rLMLJurWrfjgqhbnhrrt8apaX6gaWlHX+eVFsEoig0EEWhE7AOgHU19XwelpOOAYWHMMCUg25eddBGgbGrGvEj7WK3AsUYuwHAZAAfwFpaJAA+Tf/sCUDgnP/OrP9P+glAHwBRsBYjBsAbwKGmc/WE9fbfSABbYS1hFgAGWEe5nmm67B4AxwEsbvq9O4D/AqgCUMc5f8peX+/FqEC1Tg6AfnKHIORS1mjdUl/y8fI0CIJTrZh/+xapurXHKswNrVrRV3QZMNjcsC0XkC45ssXBxfUFn0RNDn80R2SivqXzKaFwm2YcMjxVcWJbupibABsWnT/mSTWWRUal7vHzy+nw86RaiwEsDGf0YTijvwFrAQASmJTL9SfTMbD4EPqb86D3bYAm6lLrfxGbsluBgvVn44ewzn1aAutAw+sAXgRwF4Dsi44vAPAQrN1DBOCJP/bGDGs6XxmA/QD2wlrEzgJYCCAVwK9Nk80Hwjpf6loAJ2G9hecB4N+Msds55z/Y+gu9FCpQrZMDKlDEyexWu2Q85e9rqRJFhz9Z1xIXI6/Tn7XOWWgNpamuVccxJoiielCepXHvZW8NGqVGz40FX5RPCJlVxVp5GynBHD0y3OJ7NEV1QCOx1t12bC2TSe2TfXTk6GPZwwyhYZnbw8Iy/EXREmPLa3QEArjQDaejuuF01FR8DwCwQDCf4tHH0jDw3GH0k/IR5m+AmlZTt53S4mv6t3R3vN045xlNo1AAUAlgHoBEANtgfYruwgVwXWF9us4IwNz0mh5ABWOsP+f8ScZYOYAbOOdVjLEbAbwJ4CYA3wOYf8G5ymEtY7fCessvD8BvAAJxwd6Z9kYFqnVy5Q5ASLPjSuXpxwN8z+YrlZdcQNIZ3LiXH2Rt2ENSaapr9VwhhXpIoqUx9SxgfaT5UqpMJZF7Sn7aN9jvhoGslU8fBnDPHncZRlWvVu3ZXSM02vx7y7nociav74gzeX3h65t7MDIq1axSNQzqjPOkWkuEpOiOYzHdcSzmVvwPAGCCwnCCx2RZV1Pvi0KEBBppNfX2csTPLgbrLgN1sE4SHwrrEyE5sN6Oa57MXc85T2SMvQVgI+d8XdPyBj9xzvddcC4AAOf8WNPSCGkA/ss5Pw0AjDEtrKUqGMBRWJ/sqwLQCOB5ADsYY79yzptLmt1QgWqdHLkDEHJWFM8+4e97LMNFNRSMdZM7z5X8LVVyb8vxSlNtq384MqZwEVW9jliMGZctUACQW5c1yE8dtiXKo3+r54SpoPC4zTh8yA5F9pYjYv4wMNhlJKS0NGJAaWkE3NwqTkV3353v7l6awBg09rhWR6OE2aUnsuJ64o+HqAxwacjmPU4eRHxZFvooihEYZIZSL8fSHB3MxbfQ7MEFgAbW23anANwM64jQQABvMcbG44+lBgBgAQAdY2wCgOmwPqkHxlgQgE8A/IcxdhuA+2CddP4+gHsYY/cBeAvWJ/S2N006Hwvr5PQvOee5Tde63hHlCaDNhFsnWXcTgFVyxyBdUw1j1f/28zn4u6smAYy5yp2nJaElPOetTyz6trynIGj43uzYOxJbezznhhpD5XsSWvFwx4SQWds9Vf5tnh9WIJRnrFce9OYMdl8GQqFoLI+KTj3s55fTkzH42/t6nUEDNDVH0OvUQcRXHkEv1TkEhFiYIlzuXE5mXvE1/V9w5AVbu7p40+11xjmvvMTnPAAYOeeNF7zmBsBy4WtyowLVGsm6AQAOyB2DdC1GwPi6j9fule7aXpwxH7nztNbT31k2JxznY9rynnO+/dIyes/u35b3GGvXbpZMJ1q8jgDRMCX80WMqUd2mTYUBoAHG8tUue07VM+Ogtr63PRizGEPDMveGhWX4iaLlkss1kMurhbYyE31OHUR8TTZ6upTCL0xiYojcuWQ0o/ia/ivlDtFZUYFqjWSdJ6xDiYTYHQf4Zzr3XYu9PMPMjHWo/ckY59LXr1rOirzlxTMvVKmLPnJgwD97tuU9XKovM1R9qIF1cuoVqUXtuRvD/mERmNCmXADAwfkWZdaWE0LxSDA4bB6Oj2/uwaiofWaVqr5Lz5O6WlXQlR62rqZedxyxmnL4RHAmXPH2bycyoPia/mlyh+isqEC1VrLuLEBD68S+fnZz3T/P11vbKAgdcvRheKa0f85aqcU1mC5W6xp0em/if9o8r8tQ880Wbs5v1RwnX5fQI2OD7tAzxto11yhXKEnbpDwUzB18i83VteJ095jdZ2ielO2UwefsIfTPTUN8wwl0d6uCZzfOhA4zyttKHIC2+Jr+9XIH6ayoQLVWsu5XAGPljkE6p/0uLkfmBvg2lItii/vGObN3PjTvCq7A0La+r1GlO7dz2H/bXEwkS1WBsfpTf6B1k71jPAbtGuAzrs35mtXBcG6Vy55CAzP1b+852kuhaCyPitp32M8/pwdjl38CkbTPWQQUHMKAM2kYaDiFKI9q6CI7+GrqZ4qv6U9zwuyIClRrJesWAnhc7hikczmtVOQ+7u9XmKNUDAFjHfo2jbaeV3y60OLK2rEOi0VQ1W8Z9Xa7Jsgbqr/czi2lrZ4kPtz/pi2hbjHtXq1dArdsUh7anieUjoIMt9YYsxhDQ7NSw8IP+9I8KfvhAC9ESF4aBhZYV1OP9Ky1rqZ+5U0bncevxdf0Hy93iM6MClRrJeseBPCR3DFI51AmCKVzA3wzD7i4DOssiwbes8myZVIqb3cx+W30u5b2rPUjmc+dNNZ8FQm0uszwG0L/vtdN6Tm4rde60AmhaN9mZVYkGGTbSNfHJ+9gVFSqWeVC86QcQQKTziDidJp1NXVLHvTe9XCNQjtvC9vZ+8XX9H9E7hCdGRWo1krWDYV152lC2q2Osdp5vt77N7i5DgRjbVorydl9+Yb5qNqEHu19/2+j361q7y0TQ9Unu7lU3erFLxVMWTsl/LEihaDs3p7rNathDYWrVHvKTczS+2rOc7VcXStPd4/Zle/uXhrPWMuT6ontWCCYcxB56iDizx1GP56PcJ9GqKPBmKrld9vVnOJr+i+SOUOnRgWqtZJ17gBavbcXIRcyA+Z3vD13funh3pMz1un2Q4su4Nn//fLqbif9PmpRARfa98i5ZDqTZaz9Nq4t79EqPPOvD52tZoz5tuea568NybROmbazSKyQfRNnhaKxIjJq3yF//5xYxnig3Hm6KjMUxhPofvIg4ksz0ZcVIMTfCJdIMObIxasnFl/Tf4MDr9flUIFqi2RdLgCalEfa5CsP7a63vL2CTIzp5c5iL/OWm7f2ysOoqznH5pFvH5dEVbtHhBorPzgA3tCmSfhBmqj0kQHT4pgNbqNmifm7dyqy48DgcbXnulqMSaaQ0Ky94eGHfUTR3O5RQWI7BqgajqHHyTTEl2eit1iM4EATlN3suJp6WPE1/e25kXCXRwWqLZJ1KQCulzsG6Rh+c9WkPefno6oThDaNjHQ0Cgs3fvWapVbA1c0F2jr89cNmpWubF7tsZjEeO2Cq+6nNTzH28Rq1Lc5z6Mj2XvdClawud41qb6OZSU4zudvHJy8tMirV6OJSn0DzpJxLA9S1R62rqVccQS/lOQQEm6GIsMEDJeeKr+lPT2raGe2F1zYZoAJFWnBYpTo2J8C3ukShcMjq1XIbm8YPCMBVb74rSEZDK9bEvCxRFTPQVKfMAkxtKqyHK7aO9FOHbvFTh131LThP7hZxl2FUY4rqwLYSodompexqlZWF9y8rC7fOk+q++4y7R8kgmiflHDRo1A7A/r4DsP/8a3Vwq8rkfU4dRHx1Nnq6lMAvVGKK0Dae+qBtk5JLoQLVNoflDkCc1xmFIv/xAN/cE0rl0K60yelNuySbrM4tWoymqz2HwnVUtbn+1za/7/eiFcMnhz9yQC26XfU6XAqI6inGhJHpYs6OVMXJ/mBwu9pz2kJ9vWe39PSJ3azzpPan+vufpnlSTsgNdbpE7B6QiN3nX6vmHmWH0TcnDfG1x9BDUw6fcImJV/p3R1uPOQDdwmuLZF0PAEfkjkGcS4UglD/t73t4j9plCBhr8xpIHZlPNS9+/z2LH8PVb3GSGv+v7TXu4W3e9PdCnHNuqFx0GrBEtvW9KkFdMTn80WqRiRFXk+FCpazm5I+qfbAwKcpW57QVxiRTSEhWanjEYS9RNLdpGx0iv3J4nz2MfnlpiK8/jhjXSnjpOROaH1C5tfia/t/JGrALoALVFsk6BqAMgJfcUYj8GhlreMHHa8+PWrcBHXzF4nZ7+CfLljGH27/204UO9ntsS4VXj6s+l7lh13Zz4652FTFPlf/J64Lv9WvaDd4mTDDX/aDal1Yp1A231Tltzdv7TFpUdKrRxaVuEGPoMqOnnc05+BceQv8zR9Brxpqxj+bInaezowLVVsm69QAmyB2DyMcCWN7z0u38VOfRXWKsS98CWf6a+bTSgjbvYXcpGXH3bznnP/CqCxTnFpOhclEJwIPb8/4Iba/Uwb6T4pmNb8OmKk5sSxdzE8HavlK7o7i6VuZEd9+d5+FREs+c5NYjabPScWNPdrqlUpwR/U2j7Xa3fAjprL51d9uTqA/L/dhTN7Krl6d+p6TDtipPAKAw1dnkPIyJStGl3/H2vj+3NjPhdO2hbTYJc4EEc/TIG43xpwXO8mx9blupr/fUH0qfOGr3rumms8WRWzhnRXJnIm22R+4AXQUVqLbbJXcA4njbNepDw8JDD7/g6zPYyFib59d0RrdvkSpteT6VqdYmk9EBQKEZmQDr7fZ2SS1dP7rSWLLDVnmaBXDPHncaRuq0ktqp/yJmNrt4Hjs2fPSO7Xf4nj41cKfFoqC5nx0HFSgHoQLVdnsA0H3PLuKISnny2rDgvf8I9O9bIwrtXqOos1GZeH23YvS35TmVNixQjCldBWVsxtWcY2PBF4NMkiHTVpmauUCpm2EcPqSnOWQLOK76yUN74lxQ5uf3GrZzx+09MzOuSW9sdNvLOSS5c5Er2it3gK6CClRbJVdVAsiWOwaxryJRLJoeHLh9enCgvlihSJQ7j7O5YS8/yACb7uWnNNXadFNlpevYfgBq2vt+CRaXdfmf+EpcssttrOHmHqMnmvofZRyF9ji/rZWXh/ZL3Xtz4v59k89UVflv4Ry2uedKbImDCpTDUIFqH6cefiftVyWwqocD/LZcFxbsecRFNQKM2WxUpDOZlCrZfIKx0lRn08nVTNB4CoqIq1oPp8FSG7C5eEUF57zBVrkuFCr59LnDMFLtylX77HF+e2ho0EUcSp8weveu6abi4iiaJ+Vcjo4be7JC7hBdBRWo9qEC1ckYAcN8H68tI8NDpW2umtFgTCN3JmcVXMZztQ3oZ+vzKs11apuf0+26HgAMV3OOksb8uPTy3+22srMGKu/bDSPioywBW8Bhsdd1bM1sdvE8fmzY6O3b7vA7dWrgTrNZkSV3JoK2ryJL2o0KVPvslDsAsQ0JkJboPHYk6sNKv/NwH80ZozW+WnDHZuk0g+33VFOa6m2+vQgT3AOYGHjVtzSyq1OHFdQd32yDSJfEwNg1pt6jx5v6HAJHib2uYx+CoiC/17BdO2+Py8i45lBjo9semiclGypQDkQFqn0yAJyTOwS5Omu1rqmJEaEn3/X2HG5hLETuPB0B41yKP85j7HFuhblea4/zKt0mhgNXP7Kz/dyq0XXmKrvOL9FL/gNuN4zgLlyZZs/r2EtFeWjf1L03D96/b/KZqkr/LZyjVu5MXYgFwGa5Q3QlVKDaI7mKg5p+h7VX7ZI5Mjwk7d9+vgkGQegud56OZOgRflDkaNcClS1RmBvsUqAE0TuCCV62eLSbrc//NM4smdq9xlRruMHF/07DyD7hFt/N4B3zid+GBl3EoUMTRu/eNd1C86Qc5uC4sScr5Q7RlVCBar+NcgcgbXNCqTx9fWjQ7vuDAnpVimJ/ufN0RNO3SUZ7nZuBi+C83h7nVrpN9LHFeczcpN1Q8Jmac97uNaZaQwATrzP1GzPaFLcPHB12UrDZ7KI7P0/qZDzNk7Iv+ku9g1GBaj8qUB3EOVE8d2dQwLabQgLDziiVQ+TO01FpG3hlUDkG2vcq3C63fARFUCyYm02edKs1V4RtP7fqDOfc7ms4dZeCEqYbh9UruWjz9agcS1AUFMRZ50kdHnu4oUFL86RsjwqUg1GBaq/kqnwAR+WOQS6vlrGaJ/x9t4wLC3Y7pHYZCcYUcmfqyG7aKR1isO8+boxLdltbSOl2rc3WmSqsP9H/aNUeh+xK4ME1IXcbRsUEWTy3OOJ69lZREdJnX+pNg/fvm5xfWRmwleZJ2YQBwHa5Q3Q1VKCuzia5A5C/MgLGV7y9tg6LCDX86uY6GozRpqg2MP4gt/sGpYJkbrTXuUVlZD8wl0O2Ot+hii2jShvzt9rqfFciQFBOMsWPHmqK2QWOakdc094aGnThhw9dN2rXztssRUXRWzhnHWJBUSe1e9zYk3ZZq4xcHhWoq0O38ZwIB/jnHu47B+vDir/WuY/ijPnKnamziCrixzUm9LT3dQTJdFVrNrVEqRlj0/P/VvT1sEZLvd3WiLpYL0vY0GnGweUKLnSa3RAsFpXuxPGho7dvu8P/1Mn4XTRPql3o9p0MqEBdnc0AzHKHIMAvrpoDgyNCj77p4zXMzFi43Hk6mzt/lxwyOiBKRrtNUgcA0aVXAqA4ZqvzcXDFuvyP9RK35NnqnC3x4lr9XYZREb6S+zZHXdMxBEVBQdzQpnlShxoatLtpnlSrUYGSARWoq5FcVQ3a+VpWB1xUR8aEhxx4MsBvYIMg2H2EpCsSLdwUl8t7O+Ra5ka7T8xWaIaV2vJ8RqnRa2PhlybOebv33WsrBUT1VGPiyEGmyO3gsMuTi3KqqAjpuy/1piFN86S2cN7+PQ27gBrQ/neyoAJ19dbLHaArylUozkwOCdp5T1BAjzJRtPOTYV3b2HR+QABssgxASxTmBrtvZSK6DBwMCDYdMao0novaW/rzEc65Q0dM+lu6jZhqTCgUuXDSkdd1lKZ5UqN37bxNaponVSB3Jie0btzYk3QnRAZUoK7earkDdCVlglB6b6D/1htCgwJOq5TDwJjNtxQhf3bTTslh32OFud7uC0cyJoiiy8AcW583pzYjMac2w+G31Xy5R/RdhpGBnpLrDkdf21EumCcVcPLkoF1ms7KDL+tgUz/IHaCrogJ1tZKrMgHYbE4FubR6xuqe8fPZMiY8xGW/Rj0KjKnkztQVeNXwcz41iHfU9ZQmx9yNUmiGDQaYzbdj2lv68+gqY6nDi4wSCrdbjEOH9zVHbAW/us2TnZugKCzoOXTXzhm9Dh8el9E0T6rDbMBsByYAKXKH6KqoQNkGjULZiRkwv+nluW1oRGjdOq3baDDmLnemruS2rdIRBoiOup7SVOuQ0S7GFC6iKs4uT3v9Uvh5vEkyyDJCkmiOHnWDMf6UwJnDJrXLpbIiuPe+1JuG7EudUlRZEdhV50ltGTf2ZJXcIboqKlC2sUruAJ3RCnft7kR92JnPPT1GSoz5y52nKxqZycMceT2VqdZhZU3hOiYegM1/+Ejcol6X/6mPxKViW5+7NQK5Z887DSN1WkndJR5waWz0CD18+NrRu3bexouKum+RJJYvdyYHWiN3gK6MCpRtpALoSv/R2tVmV03akIjQzP/6eg8xMdZN7jxdVZ/TUobSgkhHXlNprrPZauEtYczFXVBG2WUNpwZLTeDm4v+Vc87ttjDolbhAqZthHD64hzlkC3jXWGrFYlF5nDg+ZPSO7XcEnTwxaJfZrMyQO5OdcdD8J1lRgbKF5CoO+pvAVctQqY6PCwtOfSzAr3+dIPSSO09Xd/sWyeGb2CpNtQ6d26Z0Hd8bgF1WcC5pPBOXXrF5vz3O3VojzD1GTzT1P8I4iuTM4ViCWFjYc+iunTN6Hz40LqOhwb2zzpPaPW7sSfqLu4yoQNkO3cZrp3yFWHBzSOCO24MDos4pFAly5yGAysTro4rQz9HXVZrq1I68HhPcfJkixG5r6GRX7R1eWH9is73O3xqhkk+fOwwjVRqusslmyh1JZWVw732pU4fsS51SVGGdJ9UptsFp8p3cAeTCGOvFGBvJGHPYLf9LoQJlO1sBlMkdoiOpFISK2YF+W/4WGux7XKUaDsboz6OTuD6VH2SAh6OvqzTVaRx+TdcJUbDjjgLbzn4/qs5cLetChxqofO4wjBgYaQnYgi64undjo0dohnWeFAoLYzrDPCkOOxUoxtjnjLERTb/+D2PsXsbYZsZY6CU+P5Ux9nvTr6MZYz8xxm5mjH3PGLudMZbc9N5dTf/cfMF17mWM/aeFLKeb3reHMfZq02v3A0gGcBuAz5pe68YYS2WMbWWMOWxdQPqBZSvJVRbQ/ehWaWSs4T++3ltGhocIuzSa0WDMRe5M5M9u2CvJsgGzwlzv8OsKomcoE3132/MS6/M/7WmRTCfseI0WMTBhrKn36PGmPungKJEzi1wsFpXHyRODm+ZJJezuwPOkUseNPekMT1pOAJDIGNMCOAMgEEB3AHoAIQBymo67lXM+hnM+po3ntzS9bzCAeMZYLAA/ADM4548CGNB03EIATwO4HsDz7f9y2oYKlG2tkDuAM7MAlvc8ddsHR4RW/uCuHQ3GdHJnIn8VWM7PuDc4/vYdACjMDVo5rqt0nRgE69/q7cLMje4bCj5Tcc7L7XWN1tJL/gNuNwyXXLgiXe4s8hHEwsIeQ6zzpMZnNNS77+pg86S+lTtAk5EAlgMYyzk3wNopogEUAQgFkGuLizDGFADcADRyzhcA0DLGnsAfewDGcc43c85rrYczhS2u2xIqULb1G+hpvEv6Xuu2NzEiLOdDL90IibEgufOQy7tjs3SSAbKs8C5KJjU4t/t+eBcTFP5RTPCw6222GnNF+I5zq3M557I/FecGdcCdhlG9wyw+m8HtVxw7gsrKoN779k0dui91akeZJ2UB8LWdr7G46Xbb/Zc7gDEWA+uo01pYR6IAoB6AL4DjAAbijxGob5tuxS1uYw6xKcdmAMs4582FrBuAGy84f+UF76lrymB3VKBsKblKArBM7hjOZIdGfXh4eMihZD+fRKPAouTOQ66McS4lHOPdZY5RK8dFFa4T7D76VVB/fEB2depOe1+nNQQwcYKp/5hRprh94HD4E5fOprHRvWme1Azm5POkfhk39mShna/xWNPttk+bfn9xyeYAJsJ6uy4JwPim18/AWl5OAhiMPwYUmm/hPdbGHM238EZwzt8/f3HO0wBcC+ChppcunNenhYO6DRUo2/tC7gDOIFupPDUhNHjPQ4H+fapFsa/ceUjrDD7K00SOEDkzMC45Zj+Xi4jKsF5gmjR7Xye9/PdRpY0FW+19ndaKkYISphuH1im5SPvLAbBYlO7N86ROWOdJHZY700U+k+GaZ4Hza8JFAiiGddRpOud8BIBzjLFoWEeEcmEtUGe5HUaTGWPbGWNeAFyA89sWVTLGApl1b9QowDFz/KhA2VpyVTaALrEC8KUUi2LxjOCAbbeEBEYUKhWD5c5D2mb6NkmWhR8vxLhFlgIFAErXsQ6ZB/Nb0fJhBkt9miOu1Roe3DX0LsOo7oGSp9MUO/kJYpF1nlSfQ4fGZ9Y7xzypMsjzsNLrAN5kjO0CcBDWkaW+ANKaPv8brCNSzeXpJP48/6n5Ft7mpongV+O/ADYB2Ajg302vvQfrlmorAPxuj+J2KYzzLn372z6Sdf8A8H6Lx3Ui1QKres7P5+AWjWYwGHP4o+jk6rk18Kql71hcGODQtZgutnX464fNStc+cl2/sWLxEcDU097XUQma8inhj9QJTHTodjktyRTP7NqlONYLzPHLWDg7tbqmILr7nhOenkX9GYMcD8EsHjf25OMyXNfpMcb6AYgA8BPn3CFLddAIlH38D+jMO6L/wQgYXvTx2jIiPNSyxdV1DJWnjmvqLumQ3OUJAATJKOt/OwrNSIdszmqUGrw3FS5r5Jw71Sa4vSxhQ6cZB5cruJAtdxZn09joHpJxePzoXTtnCIUFsVskiZ1xcISlDr5eh8E5T+ecr3VUeQKoQNlHclUFgB/ljmFPEiB9rPPYkagPK/nGw300Z8xb7kzk6lx3kPvInQEAFBaDw5/Cu5Do0i8REE874loVxrPdU0vXH3Hk//Rbw4tr9XcZRkX4SO7b5M7ijCwWpfvJk4mjd2y/I/jE8cTdJpPqkAMumzZu7Mk0B1yHtBIVKPvptJPJf3Jz3Tc4IvT4Im/P4Zam1WlJx9atmJ/QGBEndw4AEM0Nsj7mzxgTFOrEAkdd73TtocTc2kynKyoKiOqbjIkj402R28Eh27w05yaIRUWxQ3bvuq3vofRrM+vrPXZy+23eLMfkcXIFVKDsZz0Aez9q6lD71C5Zo8JDDj7r7zuoURCudiIgcSJ3/i45rDC0RGlukH00RlQnDgaYw/773VOaMrraWOYUyxtcbICl24gpxoQCgbNTcmdxZlVVgb3275syLHXvTecqyoO2cA5b3go2wrpgJXEiVKDsJbnKDGCJ3DFs4ZRSkTspNGjXrED/nhWiOKDld5CORJC4uXcud4rRJwBQmOtlf7KFMVEpuvR16NYrvxR+PsAkGbMcec3W8uMe3e82jPLXSa5OWfKcicGgDc7IGD96184ZYoF1npQttlxZO27sSdpr1clQgbKvJbD+zaFDKhGFkruDArZOCQkKzlMqh8K6xgbpZK5J5wcEDj+5czRTmuqc4s+ZQjMyHoDDtl6xcLNmXf4n3pxLZx11zbZQQqG91Th0WB9z+FbwrvGQzNWwWJTaUycTR+/Yfmfo8eOJe65ynhTdvnNCVKDsKbnqLJxnz6JWq2Osdq6/75axYSGaNLXLKDCmlDsTsZ+bd8p+x+xPlKZaUe4MAMCYyk1QxjhicvB5DZaawM3FK0s557Kvx3U5g83dR91gjD/FuMOfQOugmFBcFDu4aZ5UVjvmSZ2CdUoIcTJUoOzvXbkDtJYJML3q7bllaERow0Y319Gw7rBNOjHPWl7iW42Bcue4kNJU65CNQFtD6TquPxy8tcy5xrxehyq27HfkNdsqkHv2vMsw0kPL1V120eD2qKoKjGueJ1VeHtzaeVKLx4096Vx/yyEAqEDZX3LVbgD75I5xJRzgX3q470rUhxV+pfMYzRlzmts5xL6mb5WyGOA0hQUAVKZapxnxZILGU1CEO7zMHK3aM7yo/uRmR1+3LVyg1M0wDB/cwxy8BfZ78qxTMhi0wZkZ46zzpPJ7bJUkIfcyh9aA1n5yWlSgHKOtO1A7zEZXzYEhEaFHX/fxGmpmLELuPMSxRmVwp1uGQmmqc5E7w4WUbhNiIcNcxq1nvxtVb65OdfR122qEuefoCab+WYyjSO4sHY3FotSeOpUwasf2O8KOHxt8qXlSn48be7JalnCkRVSgHGMlHLS5YWulu6iyrwkL2T83wG9gvSDYfdsK4nx650iZKgui5M5xMaWpzqlWs2eCeyATA+S4VSWsz/801iKZT8pw7TYJk3z63mEYqdRwlVPfenReTCgujhm8e9dtfdPTr2ueJ2WEE//lm1CBcozkKgOAj+WOAQC5CkX+lJCgnXcFBcSUKsR4ufMQ+dy+RXLKx6IV5jpXuTNcTOk2MQyAw+ehmLjRY0PhZwrOeYWjr91WGqh87zCMGBBp8d8M7vjvVWdRXRUQt3/flGF799z83bixJ4/LnYdcHhUox/kAgGxbVJQLQtl9gf5bbwgN8j+lUg6jJQm6NpWJN0QXop/cOS5FYWpwugIliD56JnjKMmG6xlQesePcmhzOudPPM2JgwlhTnzHjTH3SwJ1r1L2jMRrdOsU6gp0ZFShHSa7KhwwryTYwVv8vP58to8NDlKka9SgwpnJ0BuJ8Ju7nBxhk2U2+RQpLo7vcGS5F6TZRtv0eC+qPDThWva/DLGLZTfIfOMMw3OLCFelyZ+mg9iYnJ2+VOwS5MipQjvUKHHQbwAyY3/HSbRsSEVrzs9bt/9u78/iqqzv/46/PXQIJKIvKZsC6AxoXVBAlBHFBa+1iF63L3LbTdupQW1s6HZ32196OtUPbacdOpx3aapVOq6XaTlvpuCsgVVEB8QsEFRVUkMUlQBJI7vL5/XG+qTEmITe5ybnL5/l43Edyb77L+wZy7+eec77n1CFy4ECc1xSHi1ZkC66Vp42gEVSbfOfoKBIbdywyxNsVtU+/+dDMN1q2FtyaeV0ZyuAxl7fMPH585qAlKN5nly8y3/cdwOyfFVADKbnrOeDO/j7NogOGPj71PeNfuXn4sNqsyOj+Pp8pLqPf1FcPbOYk3zm6pwM691JPxavO9TrFwoNbf3N6S6b5aZ8ZchFBonNSJ82qTU96EqXBd54i8SLwB98hzP5ZATXwvtNfB15WOXjN9MOq13774JGnp0QO76/zmOJ22dLsCwIFPQZONNPsO0NnohVHnIgMCnydX8nG73715vFZzbzqK0NvHJsZN/VjrdMb4xotyLX+CswPk8mkDcIvAlZADbTkrjXA4nwecl1FxfPnjB/35Nwxo05sjESOz+exTYlR1dOe04KbuqCjSDaz13eGrsQq67wus9KSbT7oga2/3qtamK10XTlQq6qvaJl51OjscBvb07Wt2MSZRcMKKD9uyMdBtsSiWz8ybszyS8eNPnJ7LHZaPo5pStvU5/TpWJaCmzyzo0i2tWAXq41WHHcqxLxeXv5W67ajn3rj3nWqWlRji6JEKi5qPWXm6amjH0PZ4ztPAfpOMpks2A8P5p2sgPLBLe/yUG933xWJNPzD6EOWnl89buSzgypmIGL/jqZHLlmWLYoX52imdcBn/u4pEZFY5fQdvnO8uGfNtM1N65f6ztEbx2cmTL+4ddrrUY085ztLAdlMgcwXaHrG3nj9ybkVqkXY942DRy6tnXAoj1ZV1iEyuD+CmdJUtU93Vb/Oyb5z9EQss8/bnGk9ER10yukQecV3jhU7F8/a3fpG0Uxv0N5IHXr4lS0zxx+UPaBorizsZ9cnk8mC/eBg3s0KKF+Sux4CHuvJplnI/vfwA5dPO2z8m/97wNA6FRnev+FMKfrgY9lnBApqmZSuRNP7CnoQrUgkGh005SXfOQDu23rryalsa73vHL0RI1r5odaptVNSRyxHKcgLBwbIRmCh7xAmN1ZA+fX1/W3wv0OHPDn1sOoXfjpi+IyMyLiBCGVK03mr1NtEkLmKp5sLfmxPrPKMqSDeZ9vOaLryni03D1fNeu9W7K0pmcNnfKD1tC0RlYIoSj34VjKZLPiZ5s07WQHlk2uFeqCzHz0+eNDaGRMOXfONQw46rSUSOXqAk5kS855t+kJVK8f5ztFT8VTBzaP5LiKxwdGKyet85wBoTu8eu3Tb73aoasEOvt+fQ/TAo69omXnwsGxVUXZJ9sF64DbfIUzurIDy77r2d56Lx186v3rcis+MHX38rmi0INcqM8Xn8iXZopo3KJ5qLIrXpljVrCnALt85ALbv23x88NYjT/rO0RcVxA74aOv0M2rSE5ahlMt4oG/avE/FqShepEpactdTwO+3R6PbPz529CMfPnTM+C3x2DTfsUzpiGQ1XbNJJ/vOkYt4qjHqO0NPiAw6MBI/YrXvHG3qdz0247Xml4ryyrz2pqWPnnlh65SNouJ9oH4/Ww383ncI0ztWQBWARQcMvfac8eMGrx08qBaRmO88prTUBboqohziO0cu4qlGr0um5CJede5xQMFMD7Fs++9qm9N7irolCmCsjph8RUvtgUN08BO+s/SjbySTyYIf72c6ZwVUAbhk3paNiFgfuOkXH/5rtuheoCtSTRW+M/SURIYcItFxhVSwRO559aZjM5p+0XeQvhpEfNilLWecdmx63FKUUhtk/XgymczrqhRmYFkBVTiSYDPzmvwa1qg7D9nFFN85chVLNQ7ynSEX8SHnHwGF8waf0tYD791ya1RVG3xn6StBpDY9qW5O6sT1orzmO08eXes7gOkbK6AKRJAIdgDf853DlJaPLs+uFyia7rA28XRzle8MuYhEh1dL5KAVvnO0tyf1xmGP7vjTi6paMIVdX4zPHnzCZS218UqtWOk7Sx7cmUwmi36sWrmzAqqw/BDY4juEKR2zAj3Ud4beiKWKq4ACiA+5YAxQUN2lrzY/O+X53StLZlqASioOvqxlxsmHZ0YtQSnWK9f2AV/xHcL0nRVQBSRIBM3APN85TGmYvFnXV6Q5yneO3ohl9h7gO0OuIrFRRxI5oJDGQgGw+s0HZ77Z8lrJLJciSOTsVM2s2anjV6O87jtPL/x7Mpnc7DuE6TsroApMkAgW0YeFho1pc9mSzBu+M/RWNJsehGrRzQMUrzqvIFvOHtj669NbMnvX+M6RT0dkR59yacuZ6QqNPeM7Sw5eBf7NdwiTH1ZAFaargYJeTNUUtnha9x29lRN85+ijRt8BchWNH3Y8Mvhp3zk6UrLxu1+96dCsZopqQtX9GcrgMVe01E6uzoxcihZW92kX/jmZTJbzmn8lxQqoAhQkgvXAj3znMMVrzkpdJTDMd46+EM0W/nounYhXzc74ztCZlmzzwQ9u/U2zqhbl77UrESKx81Mn19WmJz2J0uA7TzeWJpNJm66mhFgBVbi+BWz1HcIUp/c/nh3sO0NfiaYLZnLKXEQrJp4C8XrfOTrzZutrx6x8475AVYuhtSYnx2bGTf1o6/TGuEbX+87SiTQw13cIk19WQBWoIBE0YldqmF4Y1aBbhjVzku8cfRXJFmcBBRCrnNHgO0NXXtjz9OkvN9WX5CX0w7Sq+oqWmUeNzg5b5jtLBzcmk8mCWHja5I8VUAUsSAS3A0t85zDF5eNLshulBP62o9nWohtE3iY66KRpEHnJd46uPL7zrll7Um8+5jtHf4gSqbio9dSZp6eOfhQtiMmJt+B6FEyJKfoX2TIwlwKa4dgUOFWd9qwe4TtGPkTTLUV7IYWIRKKDpxb0gO17t9xyYjrbusF3jv5yfGbCGRe3Tns9qpHnPUf5cjKZLLoLIsz+WQFV4MIB5fN95zDF4bTndU0sy3jfOfIhltlXkIOxeyo2eNo0kIJdeiSj6aq7t/zyQNXsTt9Z+stIHXr4lS0zq0dmhy73FGFxMpn8nadzm35mBVRxuB5Y6zuEKXyXLCvOK9c6E0s3F+tM0wCIRCuig054zneO7jSnd41buu2Obara4jtLf4kRrby4ddqMKanDl6MM5Li6N4HP9vdJROQ0ETm93f0KETlSRK4UkZG9OJ508lhlD/ctq5qirJ5ssQoSQSvwSaCoP5Gb/lW5T3eP38nJvnPkSzxV/LVgrLL2VNwbacHavm9TzdqG5QU3g3q+TckcMeMDrae9GlEZqLFpX0gmk/3WAikiERGJAYcD54eF0wTcUjGrgC8AU8Nt7xSR4SJym4iMEJGVIrJcRP4kIr8WkRHhdp8E/l5EzhCRW0XkVBEZDtze4dxJEZkuIqNFZLyIfElEvgpcJyJ1PS24ip0VUEUiSARPAd/3ncMUrg+syK4RKMiZsHsjnmp61yfhYiNSMSQSP6bgZ8pe3/DojG17N5XklXntHaIHHn1Fy8yDD8xW9vcA+v9NJpO/6edznIi7yOgfgbOBB4HJwB9UdZiqnqaq94TbCq6wasVN0rxWVWeo6gdU9QpVfUtEZgCzgLuAzwHNQCI8z4sicryIjG53/hRwFvBx4DRgCtACTAPab9drInJju++TIjIrH8fNl5jvACYnSeADwCTPOUwBmrNSh/vOkE/xVGNJfMCLV519Ysuu5xqBob6zdGfZtt/NuGj8VU9Vxg441XeW/lRB7ICPtZ4x/fHYc8vWRl85HaEiz6d4HVeA9CtVXS0iv8UN75gE7AaeAj4lIoPf3kxbeOeFSAIcEhZMAGlVfRx4FNgG/Aw4HdfjkQ2Puxe4Bfi8iAwBxgHHASOAT4THFGACsF5VN+XpOV6Tj+P0l5J4gSoXQSJoAT4FRbsKueknE3boi0NaqPGdI5/iqaaS+IAnkcoRkdiElb5z7I+i0bu33Hx0RtMFO/1CPp2ePmbmha1TNopKvq+W/HwymdyR52O+i4h8Gle8fAf4BnAN8GHgVFyxUw9cGW5eCdyD6+67EjgG+AFwDvCfAKqaBa4DFuK6/74YHv9s4F+BNaq6AjgMOBTX2jUYeAnYCLwArKabq8ZF5EkRGSUi20VkrIj8n4hUhV2My0TkJx22X9LhEF8WkaUi8lsRiYbb/FhEHhGRu9q6Ijs5r4jIT0TkryKyRETGdLZv+LPbROTB8PYfXT0XsAKq6ASJ4HGg239UU34ufzj7su8M+RZPNea7ZcCb+JDzjsF1nxS0VLZl2H1bFqKqu3xnGQhjdcTky1tqhw7RQU/k6ZB3JJPJRXk61v7cjBvj9EPcPFPTgLtx3XpXAytU9aZw232qOktV64A/4BasfxX4HrAJQETeB7wfeAVXEG0M983iWrgiAKr6MPAkcAewHTgSOCr8OgXXEtWVl4A5wBPAebixWp/FdSnOBMaKSHdreD4VPoddwEVh5sGqWgvcCfxzF/tdBMRU9Uzg34FTutn3X4DxuN6ek7rJYgVUkfo6UNBX95iBE8lq+sSXdLLvHPkWTzUN8p0hXyRy4FiJjlrhO0dP7E69fvhjO/+8UVXL4qKVwcSHX9py5mnHpMcuRfs0594O3HikgXImsAxXPH05/P5i6HQ9wLbWlZVANa7wiQMnAEG4zSZgAW4R7/8AbgXG4K4CvwJ4tpPjbsF1V16Na7G6EehuyohVwMeAvwAfBVYCxwIfClubjsC1bnWl7W9oFa5gm9zusRV0PbxlIq5oQ1UX4wrNTvcNux+3qmoj3ReDVkAVoyAR7MP9hy7aiQZN/sxcq6siyijfOfItnm4q+vX82osPOb+aIul+f6Vpwykb96zyNXfSgBNEZqYn152XOnGdKNt6eZirksnk63kN1g1VXQ68CPwK+B1uEPlbdD7lTVpVZ+GKpONwrUvPANcC94bHWwu0XfragOsSPBRYB3waN7i8vSrg2+Ht67juv+/iutl+0EXs1biB5/fjWqJW4QqzG8N8Xwe6a00/Jfx6Qvhc1uHGaxF+7Wq5nA24ge6IyOW4orCn+3bJCqgiFSSCJ3H/2UyZ+/DybMktDAsQTzUP8Z0hnyLRgw+XyPCiaIUCWPXGA3Vvtmx7xHeOgTQhe/CJH2+ZER2s8VU57np7Mpn8Q7+E6oKIXAFsxhVRr+K6iD9ChxYgETkAaHuNEOBcYCmueJkBtF98WXAtQk24AeLTccXTJqC2Q4RmVZ2Ka9n5blgA3Qp8RlXndRF7Fa5AegnYoaqbgV8AF4jIMlxr1ivdPO1aEVmKu8rvT6r6F2CviDyCG//1fREZKSI3ddjvLkDDc1yJK9jetW835+1USQzSLGPfxw0CPNd3EOPHsCZ9fdQupvjO0R9i6dIqoADiQ84f0brnt75j9NiDW/9n2gcmXP1MRXRwd+NSSkoVgw65vKX2oIfia5e8FNkxE9lvQ8NW4PMDka2DO4GDcGORvoQrpE5X1edEpBpo6wI/C7gv/L4C19LyfuBDuILlQRH5kqo+Gu5TiWuheRHXJfgybmzTD0XkHFV9AIjydv0wHxgmInNw3XO3dBVYVXfius4g7KpT1aZwv862n9Xu+2QX21zdycOf7rCNAlf1YN9Z7c/b/vydEXdcU6xqFtaMAdZA6XXhmP371L2Zpeev0jrfOfqDgj5c91/QyczIxWxfw8+eQpuKZqqAwdEhOy8a/4+tEYl0NzalJL0Y2b7yofjawxAO7mKTDDA7mUwuG8hcuRKRmKqm290/CtikqmkROQTY3dls9CISCa/O68k5huFqioZ85S501oVX5IJEsA13qalVwmXorGd0rO8M/UVcd0LJLcIarzo77jtDLvZlmg558LVfN4YtBWXliOzoUy5tOTNVobGuJkP9VqEXTwDti6fw/sa2x1R1Z1dL+fS0eAq33VVOxRNYAVUSgkRwN+7qB1NGJr6i9YPSHOM7R/8qvTftaMVRJyIVRbW25Zstrx276o37Ay3DLouhDB57RUvt5EMzIzvO1P4gcIOPTKYwWAFVOq7FDdAzZeKyhzM7fWfobxHNlFwBBRCrrGv2nSFXG/esPv2Vpg0lv9xLZyJEYhekTq6rTU16AmUXbhqAK5LJZFFcVWn6hxVQJSJccPhSSrDLw7xbLK0tx26h5Af2Sja9z3eG/hCtOP40iG7c/5aF5bGdf67bk3qrv9eRK1jHZsZN/Wjr9IYqHXRpMpns7XQHpkRYAVVCgkTwPG7xx7JrZi83c1bpKoHhvnP0t0g21enYjGInIhKrnL7dd45ekHu3/PLEdLa1s0kVy8IwrfrFV7913RLfOYx/VkCVmCAR/AF3WakpYe9/PFsyy5x0J5ppKfjlT3orOujUaRDJ9zps/S6j6ap7tvxyqGq25LuQO7EYt/acMVZAlaiv46aqNyXokAbdOryJk33nGAixdEtfltYoaCKRWHTQyS/6ztEbTeldhy7dfsc2VS3ZArcTLwJXVs+vtRZ+A1gBVZKCRJAFLsOtjm1KzKVLs89LmfztxjLNJT1IN1Z55lSgKFtytu/dVLOu4a/5WoS30O0DPlw9v7bBdxBTOMriRbgcBYmgAfggb69tZEqBqk7foO/xHWOgxFLNJf1pXyQ2OFIxOec1uArFuoa/zti+d3M5XJn3uer5tU/7DmEKixVQJSxIBGuBT/rOYfLnlI36TCzLYb5zDJR4qvTr/3jlrJOB3b5z9NbSbYtm7E03rvSdox/Nr55fu9B3CFN4rIAqcUEiuAP4nu8cJj8uXZbd4zvDQIqnm0pqGZfOSGTwsEj88KKdw03R6N1bbjoqo+mXfGfpB3cA/+I7hClMVkCVh+uAv/gOYfqmskX3TNhRHoPH28RTjWWx4Hm86tzjcONsilIq2zLs/i0LUdVdvrPk0Qrg72zQuOmKFVBlIBxUfgk2U3lRu2hF9mmBIb5zDKSKVGNRrRvXWxIZeohExxX1gOxdqdcPf3znXc+rasZ3ljzYBLy/en5t0Ra1pv9ZAVUmgkTQBLwP2Ow7i+mdC57S4b4zDLR4a9Mg3xkGSnzInCOAop624eWm+lNf2LN6ue8cfbQLeG/1/NodvoOYwmYFVBkJEsFrwHuBBs9RTI7G79CXhrRQ4zvHQIunGwf7zjBQItER1RIZucJ3jr5a+cb9dW+1bC/WIioNfKR6fm297yCm8FkBVWaCRLAeuBgopwnwit5lS7Jl2XIYTzVX+s4wkOJDLhhFCSzF9MDWX01tzewLfOfohauq59c+4DuEKQ5WQJWhIBE8DHzKdw7TM5GsZk56USf6zuFDLN1cVmO+IrHRRyMHPOk7R19lyVbcveWmMVnNbvWdJQffq55fe5PvEKZ4WAFVpoJE8Bvcki+mwM1Yp6uiyhjfOXyIpfcO9Z1hoMWHnFcSrW77Mk2HPPTab/aoarPvLD3we+Ba3yFMcbECqowFieAG4Oe+c5jufWR5thSuauqViGYqUG3xnWMgReOH1SCDn/adIx/eaNl67Ko3HlijqoXcLbkMW+PO9IIVUOYq4Le+Q5jOHdCsb45uYIrvHH5po+8EAy1eNbuor8Zrb+OeVdNfbX6uUJd7eQq4qHp+7V7fQUzxsQKqzIVzRF0J/Nl3FvNuH1meXStQ4TuHT6LZ0l/PpYNoxcRTIb7Bd458eXTHH+saUw2P+87RwTrg/Or5tUW7jI7xywooQ5AI0sDHgPt8ZzHvNHuNjvadwTfRTFm2DsQqz3zLd4Y8knu2/LImnU096ztI6EXg3Or5tW/4DmKKlxVQBoAgEbQAHwIe8Z3FOMe8qhsGpTnWdw7fItlUWc4GHR108jSIbPKdI18ymhpyz5ZfDlHV1z1H2QKcUz2/9jXPOUyRswLK/E2QCJpxs5UX/WXUpeDyJRmbCRmIZlrLcs4yEYlEB5/2iu8c+dSUbqhetv3Orarq69/0NWB29fzaUlz42AwwK6DMOwSJYDdwPlCMk+CVjFhaWya+Un4zj3cmmmlJ+c7gS2zw6dNASqqlZNveF09Y3/CojxnXt+OKp+c8nNuUICugzLsEieBN4BygZAaxFptzV+sqgRG+cxSCWHpv2U7jIBKtiFbUlNwb/tqG5bU79r68bABPuRM4u3p+rb2mmbyxAsp0KkgEO4A64BnfWcrRBx7Pxn1nKBTlXEABxKpmngKU0oByAJZs++2Ze9NNKwfgVG/gxjytG4BzmTJiBZTpUlhEzcLGRA2og3fpayMay33up7fF083iO4NPIhVDI/GjS+6DjKLRe7bcdGRGM5v68TTbcS1PJff7M/5ZAWW6FSSCt3DdecW6unrRuXRp9lmxv82/iacay7qAAohXnV0DlNx8WK3ZfcPv37Iwq6q7+uHwm4AZ1fNr1/TDsY2xF2mzf+HA8jmArVI+AM6o18N9Zygk8VRj1HcG3yRSNTISG/+U7xz9YVdq5xErdi5+XlWzeTzsOlzxtDGPxzTmHayAMj3SboqDxb6zlLKTN2bXxLIc5jtHIYmnmmK+MxSCeNWcY4CSnNJhc9P6U1/csyZfc9CtAGZWz6/dkqfjGdMpK6BMj4WTbV4M3OE7S6m6dFl2j+8MhaYi1VjWS9m0keiBYyU6ysfl/wPiqTfurWto2dHXoQIP4AaMv5mPTMZ0xwook5MgEaSAjwM3+85Saga3auN7tnOS7xyFJp5qHOQ7Q6GIDzm/GshnV1dBuX/rr05rzezr7Rx0dwIXVs+vLbvFp40fVkCZnAWJIBMkgk8D/+o7Syl53wp9WmCo7xyFJp5qqvSdoVBEogcfLpFhJdsKlSUz6O4tN4/OajbXyUNvAi6pnl9bkl2cpjBZAWV6LUgE3wQ+C5T1PD358t6nsgf6zlCIYulmK6DaiVfNGe47Q3/al2kc9fBrtzWoanMPd/lu9fzaz1TPrx3QljkRubHd90kRqReRZSLyoIiMCx+bNQA5RovII+3uTxCRJSLykIj8XETK/irW/mIFlOmTIBH8AvggJXiJ9UCq3qmbhu7jBN85ClEsvdda5dqJxKsnIVUDMQGlN6+3bJm0+s0H9zf9gAJfrZ5fe+1AZHrXyVWv6fDQDao6E7gFuHogMojICGAhMKTdw/8AXKWqs4HxYEtC9RcroEyfBYlgMTATt1Cn6YXLlmQ3+85QqKKZliHk9xL3ohevOqfkX7uf371y+qtNzy3p4sd7gUur59d+fwAjvYOILOniRyNw+QDOFZGlIvK0iIwRkUEicnv42G9EpCJsqbqhw3ZVInJn2KL1k25iZIBLgN1tD6jq11S1Prx7EPB6H5+q6ULJ/xGagREkglXA6cBa31mKTSSr2ZNf0GN85yhUAgLYwOB2ohVHnQwVJb80yV93/G9dY6rh8Q4PvwbUVc+v/Z2PTN34mogsw70O/ih87ChVrQNuA2YDnwHWho89B3yqi+0+G243ExgrIp22Tqvq7q4mIRWRS4B1qro1P0/PdGQFlMmbIBG8DJwJ3Os7SzE5o15XRZWxvnMUtqx1EXcQq6orh6JS7tnyy5p0NtW2oPJqYGr1/NpCXF7qBlWdqaqXtytqfhV+3QFUAJNx81QRfp3UxXbHAh8KW7mOAA7NJYiIHAF8Bbgm96dhesoKKJNX4azlFwLemtaLzUcfyaZ8Zyh0kWy2pwOKy0a04vipEC35mbYzmhpy75ZfVqWzqV8DtdXza1/1nSkHHQv/dbgWKsKv67rY7lngRlWdBXwdeLmnJwzHRd0OfKqflsgxISugTN6F0xx8FbgUsDe+bgxt1rfGvGULB++PaHrv/rcqLyIiscGnb/edYwBoY7rh5t9v/uHfVc+vLfaWyJuA48KuvqOBW7vY7hfABeF2nwNeyeEc1wITgB+HV+PV9SGv6Yaoqu8MpoTVLKw5AfgjYOu7dSJxf2bZhU/pTN85Ct3y6d9Z2Tpo2Cm+cxQa1Wy6peFH20CrfWfpJ3uAv5u3aPEffQcxpiNrgTL9KkgEzwCnYgsRd+rsNTrKd4ZiEM222gSJnRCJxKKDTn7Bd45+shE43YonU6isgDL9LkgEbwLnY+Oi3uHoLfrs4BQTfecoBtH0PpustQuxyjOnAjt958ize4DT5i1avN53EGO6YgWUGRDtxkV9HJt0E4DLHs5s852hWMTSe20eqC6IxCsjFZNKZUqDDPAN4MJ5ixY3eM5iTLesgDIDKkgEvwVOAZ72HMWrWEZbJ71iMwT3VDzdZIM1uxGvPOtk2k2mWKQ2AzPnLVp8/bxFi61gNgXPCigz4IJE8CzuEt7/9J3Fl7NX68oIjPSdo1jEU9Zo2R2JDB4WiR2+yneOPvgdcNK8RYsf9R3EmJ6K+Q7gk4iIdrgMUUQqVXW/l0yLSERteYleCxJBC/DFmoU19+PWjjrYc6QB9cHHsmX9t5ereKrJPuztR3zIuZNbdv18HzDYd5YcNANfmLdo8c2+gxiTq7J9URKRTwJ/LyJniMitInKqiAzHTUDWfrukiEwPV7weLyJfEpGvAteJSJ2I2ErxfRCuo3cisMRzlAFz0G7dNrLR5n7KRTzVaAXnfkhk6CiJjn3Cd44crAamWPFkilVZFlAiMgOYBdyFm6SsGUjg3shfFJHjRWR0u11SwFm4AdCnAVOAFmAa0H67vmS6sd33SRGZlY/jFoMgEWwFzsYNHi35q60uWZbdIBD1naOYxFONcd8ZikF8yJz3UPh/QwrciJui4FnPWYzptXL9VPcosA34GW4sTgbI4gZh7sV1KX1eRIYA44DjcCtsfwK3sKngZnpdr6qb8hFIVa/Jx3GKVZAIssD1NQtrHgIWAkd6jtRvzlyvh/nOUGwqUo0VvjMUg0h05ASJjPyrZt8803eWLuwAPjFv0eK7fQcxpq/KsgUqHLt0He6N+gvAF3HF0dnAvwJrVHUFcBhuEcfJuHEFL+Emd3sB1/yc7uocIvKkiIwSke0iMlZE/k9EqkTkThFZJiI/6bD9kg6H+LKILBWR34pINNzmxyLyiIjcFa531Nl5RUR+IiJ/DafxH9PZvuHPbhORB8Pbf+TyO+wvQSL4K3ACboB5yV15deIL2WfiGZuVPVexVHMxjevxKj7k/FEU5t/O/cCJVjyZUlGWBZSIvA94P259oY3hDVwr1CTC34uqPgw8CdwBbMe1ihwVfp2Ca4nqykvAHOAJ4DxgFfBZYK2qzgTGisgJ3ez/lKrWAbuAi8LMg1W1FrgT+Ocu9rsIiKnqmcC/A6d0s++/AOOBDwAndZNlQAWJoDlIBF8E6nj736YkfHxpttgvNfcinm6q8p2hWERiY45Ghj7pO0c7u4GrgDnzFi22uc9MySjXLrxNwAKgEdeNNww3S/b1wBW4lbA72oIbLxXDjV8ZDnTXrbAK+BjwF+CjwM24QuqMcHzTcFzr1jNd7L+i3XGODM+5ot3PLu5iv4m4og1VXSwiEeArne2rqptEZKuqNopId8WgF0EieCRcS+87uJbCoi74B7Vq0+HbC6dQLSaxdPMQ3xmKSXzIeZWpxj/4jgHu9e9z8xYtftV3EGPyrajfkHpLVdfy9mzYDcA1uGJmHfBp3ODy9qqAb4e3r+O6/76L62b7QRenWY0beH4/riVqFa4wu1FVZ4XHebmbmG0Lp56AK/jW4cZrEX7taubhDbiB7ojI5biisKf7FpwgEewNEsGXgFrgOd95+uLCJ3W1wFDfOYpRLL3Xfm85iMbfU4MM7urD2UB4Hbh83qLF77PiyZSqsiygQgIciyukRgDTccXTJtybdXvNqjoV17Lz3bAAuhX4jKrO6+L4q3AF0kvADlXdDPwCuEBEluFas17pJl+tiCzFXeX3J1X9C7BXRB4BPgx8X0RGishNHfa7C9DwHFfiCrZ37dvNeQtSkAgexXUz/oDCv8qoUxc+kT3Ad4ZiFdFsHNV9vnMUk3jlWb4WYL4dmDxv0eLbPJ3fmAEhHeaRLBsiksS11qwBXgRuApYCvwR+CCxW1QdE5HrgL6r6uIiMwnX3HQH8B3BBWBiZAVSzsOZE4KfAGb6z9NS4N3TzjT/P2NV3ffBQ3Y9fRyJlNeFqX+176z+fhfSxA3S6jcDceYsW3zdA5zPGq7ItoDrKZWZxERmG+9019G8q05WahTWCm7vru8Aoz3H26yt3ZpZOfV7rfOcoZg/P/NFmjcSsCM1Bet/KR9N7l/b3B41W3N/hd+YtWmythKZslOsg8nfJZVkWVd3Vn1nM/gWJQIFbaxbW/BE3Nu1zFOjklKKaPWWjHuM7R7GLZNN7MxF7ycpFdNDJ09J7H9kM2f4qPB8GrrIJMU05KucxUKYEBImgIUgEn8cNnH/cd57OTK/X1VFlrO8cxS6STVvrRo5EItHo4FO7u1iltzYBl81btHi2FU+mXFkBZUpCkAhW48ZE/T1utuOC8bFHsi2+M5SCSLbV16DoohYbPH0aSL7mX3oLNy3KxHmLFt++v42NKWXWHm5KRtit98uahTV3AP8EfBnwOn/Q0L3aMPbNv01JYfoglmlJWyWaO5FoRbTi+GczrcGYPhymBfgv4IZ5ixa/ladoxhQ1a4EyJSdIBHuCRPAN3KzxC+hmyZ3+dvFfs88IDPJ1/lISTe/19u9Y7GJVdafg5rzLleKmJZg4b9Hir1jxZMzbrIAyJStIBNuCRHAVcDzgZVrms5/WQ3yctxTF0812yXAviVQMjcSPejrH3ZYCU+ctWnzZvEWLN+U/lTHFzbrwTMkLEsGzwIdrFtZMB74HzBiI8x65VZ+rTDFpIM5VDuKppv1vZLoUrzqnpmXXxmbcygrdqQf+ed6ixR1XZDDGtGMtUKZsBIngsSAR1OIWkl7Z3+e7fEn2tf4+RzmJp5oKbr3GYiKRqoMiseruFhneipsOpMaKJ2P2z1qgTNkJEsFdwF01C2suAP4fbhmfvIpmNDV5sx6f7+OWs3iqsSDn+Somsao5R7fuvjkFxNs9vAk3EeYt8xYttnH6xvSQFVCmbAWJ4G7g7pqFNbNxhdSsfB179hpdGXl7AWeTB/FUo71e9VEkOmycRA9ZrpmdM3CLc/8b8Ot5ixbbAH1jcmQvSKbsBYngIeChmoU1M3CF1Hl9PebFj2attSTP4qmmCt8ZSkG86tzG1j23fRz43bxFi3u8AoMx5p2sgDImFCSC5cCcmoU1U4HrcGOlch4nOHK3bh+5hyn5zlfu4qlGmw6ibx4Gvnv1TZfdC5f5zmJM0bNB5MZ0ECSCJ4JE8CHcPFI/BHJa+/Bjj2TrpUDX5Stm8XRzpe8MRSgD3AlMnbtg9uy5C2bf6ztQV0TkxnbfJ0WkXkSWiciDIjIufGzWAOQYLSKPtLs/QUSWiMhDIvJzEen0YgYRuVVEVovIIyJyl4gM7WOOJSLy/fD7x0Uk2ZfjmfyzAsqYLgSJ4KUgEcwDDgXmAj1a86t2nU7o12BlKpZq8jqrfJHZDtwAHD53weyPzl0wu7ur7wqCql7T4aEbVHUmcAtw9UBkEJERwELeuYLBPwBXqepsYDxQ080hrlbVWmAFcHkeIp0gIpH9nNN4Yl14xuxHkAiagJ/WLKz5b2AO8MXw67s+ida8lA3iGXux6w/x9N4+faIvE48APwV+P3fB7JTvMLkQkSWqOquTH40A9uI+8J8rIt8ChgHn49bmuxUYB7wKfBL4F9xVhjPabbcb+BUwCghUdW4XMTLAJcCf2h5Q1a+1+/lBwOs9eDojgJdF5D24QrY1PNYnReQgXJE2DFjZSeHYXgzXEr4ZQETGAbfhXnuWq+rXRORyYArwTWAZUKeqe3qQ0fSRFVDG9FC41t49wD01C2uOBf4RuAIY2bbNZUuyDX7Slb5otrUK1Qwi1j36TnuAXwM/nbtg9lrfYfLoayLyWeAV3N/al4CjVLVORL4KzMb97a1V1Y+LyDeBT4X7dtxuVLhdUkT+ICInqOozHU+oqrsBOuulE5FLgHWqurWbzD8WkUZgLW4JnEOBi4DzVPXxcJvrgNtV9TcicouInK+q93RxvK3AObw9b92hwNeBp4FHga+Fx7kS+BHwXSueBo4VUMb0Qji7+RdrFtZ8FfgQ8OmKlE47Yhsn+U1W8hpxn9yNe5P+b+B/5i6YXYpvmjeo6q/b7oRFza/CuzuACmAyby/TtAK4ANcq1XG7Y4EzwjFUw3GFyLsKqK6IyBHAV3DFTHeuVtXlHTLf1654Isy8oF3mSbgPZp1ZDXwCV4wNw63r+U3c38EB7ba7CfgJ8Jn9PxuTL1ZAGdMHQSJoAX4L/PbrnzvuMHEvdn8HHOE1WIkSzTaqRMu5gHoN92b667kLZq/2HcaDjuv5rMPNt/ZA+HUdrjuv43bPAk+o6i0i8j7g5Z6eMBwXdTvwKVXN6YKSUGMXmTeGX2/rZt9VuLm6vgacCXw5vL+GsAAUkRjwBeB/cGM1f9yLjKYXbBC5MXny7QXrNk/aUP8t3JiFmbhPhbv9piotopm9vjN4sAc3ZuZcoHrugtnzyrR46sxNwHEisgw4GjceqjO/AC4It/scrluwp64FJuC655aISF0f8oIrgC4VkeVAg6re1822q3CFUtt4tsW41qs/A80icihwTfj4dcAVIlLdx3ymh0TVFjg3pr/UT5xUCVwIXAy8j3c2u5scLZvx/bXpWFU5LJGTAu7FjW3689wFs8uxcDSmoFkXnjH9aNKG+r24eXjurJ84aRBuDMWHcZN0HuQzWzGKZFItJfyq1QosAf4I3DF3weyeXO1ljPGkdF+KjCkwkzbUtwB/Af5SP3FSDKjDtUx9EDduw+xHNNPS6jtDnr0J/B+uS+aeEh0MbkxJsgLKGA8mbahPAw8CD9ZPnPR5YDqumHov7qoc04lYZl/Gd4Y82IgrmP4MLJ+7YHYpPCdjyo4VUMZ4NmlDveLmdHkU+Er9xEnjcF195wBnY61TfxNLNxdjsbEXWI67UuyuuQtm13vOY4zJAyugjCkwkzbUb8XNY/MrgPqJkybxdkE1CzjQWzjP4qlm3xF6IgU8RdjCCDw2d8HsFr+RjDH5ZgWUMQVu0ob6eqAe+HH9xElRYCquZepM4DTKaDB6LNVxep+CsA83IeKy8Pbo3AWzi6LSM8b0nhVQxhSRSRvqM8Bj4Q2A+omTjsQVVW23k4FKLwH7WTzd5HvuujRuIsSVuFamp4BnrIXJmPJjBZQxRW7ShvoXgBdwsyUTXuF3PG8XVKfhlo8o+r/3ilTjQD6HDK7lr61QWgk8PXfB7H0DmMEYU6CK/gXVGPNO4RV+T4e3nwPUT5wUB47BFVLtb0cBg33k7I14a2O8Hw67F3gOt9xH+9t664ozxnTFCihjysCkDfUpXNfTuvaP10+cFAHG44qro8OvR+AWWx2HW8Xed7fZ38RTjYN6uetbwJbw9jzvLJRembtgti3JYIzJiRVQxpSxSRvqs8Dm8HZ/x5+H3YFjcMVUW1HV/vuxuKsCDwhv/fqaEk83tW8tawIawtvrwNbwtqXj99btZozJNyugjDFdCrsDXw1v+1U/cdJgXCE1lLeLqva3GNDW2rO/rylckdTY9rWidc8e3OK6DXMXzE737lkZY0zf2WLCxhhjjDE5KpixDcYYY4wxxcIKKGOMMcaYHFkBZYwxxhiTIyugjDHGGGNyZAWUMcYYY0yOrIAyxhhjjMmRFVDGGGOMMTmyAsoYY4wxJkdWQBljzAATEenkscoe7Gev2cYUCJuJ3BhjBpCIfBKIAuuBzwL/BWwEblXVD4bbJIF7gReBCuAjQDy8LQeeAFpwiySv7uJUJ+EWg54I3Adswi2T81PgU0Am3K5ZVd8fnvdO4NPhNnOBB4C9wBu4JXSuVtW3+vgrMKYk2Fp4xhgzQERkBjAL+Crwfdw6fwngTuBFETke2BlungLOAibgiqEI8BQwDdisqptEZA0wG0BVs+E5JNz2QSAdHuceYBEwHbgd+E277SvaRwT2Aa3hfmtVNZHnX4MxJcEKKGOMGTiPAtuAnwGn41qBssBuXEvPLcDngXHAccAI4BO4wkZwxdR6Vd0UHi8LXAjMFZEJwC6gAfgVuKJKRNq6Gc7CFVJ/K7ZCaRGJqWoaV3C1EeCQsOgDSKvq433+DRhTIqyAMsaYARIWNNcBC4HbcAXQW8ANQB0wGqgCDgUmhz97KdwuguuGi3Y47F+Au4FrcC1Uy8Pt/6HDdjOAnwMPi0gGOBFYG257E/A/QCWuyBLgSuAY4Afh8d8LTO3r78CYUmEFlDEDQERGAi8DB6vqvv1smwSWqOqSHM9xo6pek6/jmfwTkfcB7wf+G1e4ZIGDwq+TgIiqPiwidcBioAY4Ejd2SYCRwDMdDlsD/DswHvgYbqzStZ2c/nfATOBc3Pip+4EPAllVbQ632dduPNQYXNfhQcD3cAWdMSZkBZQxA+NcYBDuDey+/jhBZ8WTKTibgAW4sU8/A4bhxkJdD1wBPNth+y3A53Cv1VFgOG5Q+d+o6hrgXBH5Cq5F6YPAyk7O/SfgR7jWrdfCxy7E/d/8dHh/hIgsAQ7AtWBtB8YAJwBBrk/WmFJmBZQxA+N84CfA+SJyBu5qqhm4N9DzcS0Cd+DeJAVYAhC+mT0JnKCqc0RkEHArbozMq8AnVbW1bVtVnRV+P6Kz4xm/VHVt2AoFbqzSN3HdYo/gBnef0W7zKuDbuAHdbWOT3gO8JSInqeo8ABH5f+F+Q3D/l1qBZIdTHwj8Edfy9WmgFrgU112XFJGjVHUjbpzTuSLye9wYrI24/z/XAt/p8y/AmBJic4oYMzCm494Mzw7vH6WqdbhxMLNxl7MvVtWzcFc/tTkdeExV54T3P4O7MqoOeA53OXpnujqe8U+AY4Em3CDx6biiZhOusGnTrKpTcVMWfDcsjm8FPtNWPAFRVb1eVS9Q1Zmqeo6qvldVvwF/mzcqihukfla4z59UdS/uA3QG1/33ERE5ANdV2JbxXGApsApX7K/P62/BmCJnLVDG9DMROQE4GHep+ntwY1V+Ff54B65L5nDcGBVwA4HbrFXVP7S7Pxlou78CuKCL03Z1POPfINxg7etx8zxdjBsfNwX4oYicgyt62l6f5wPDRGQObozTLfC34uiEsJWyMyfxdtcfqvqmiNwKREXkpnCbZlW9OTze+3m7e7kCWIcbr/UhXDfigyLyJVV9tI/P35iSYBNpGtPPROSfgIyq/lBErgc+CVyhqktE5BPhZmOBPar6XyJyN67FYUn7brnwWHOBEar67XBw+FZV/Xn4s/ZdeNd1drwBecImJyIS6TCtQFfbDcO9Zje0e6yirQs3T1napjNou38UsElV0yJyCLBbVVvydT5jipl14RnT/+YAD4XfPwR0NpfOL4APh60JB3ZzrJuA40RkGXA0rkunMz09nvGsJ8VTuN2u9sVT+FjeiqfweOkO9ze2PaaqO614MuZt1gJljDHGGJMja4EyxhhjjMmRFVDGGGOMMTmyAsoYY4wxJkdWQBljjDHG5MgKKGOMMcaYHFkBZYwxxhiTIyugjDHGGGNyZAWUMcYYY0yOrIAyxhhjjMmRFVDGGGOMMTmyAsoYY4wxJkdWQBljjDHG5MgKKGOMMcaYHFkBZYwxxhiTIyugjDHGGGNyZAWUMcYYY0yOrIAyxhhjjMmRFVDGGGOMMTmyAsoYY4wxJkdWQBljjDHG5MgKKGOMMcaYHFkBZYwxxhiTIyugjDHGGGNyZAWUMcYYY0yOrIAyxhhjjMmRFVDGGGOMMTmyAsoYY4wxJkdWQBljjDHG5MgKKGOMMcaYHFkBZYwxxhiTIyugjDHGGGNyZAWUMcYYY0yOrIAyxhhjjMmRFVDGGGOMMTmyAsoYY4wxJkdWQBljjDHG5MgKKGOMMcaYHFkBZYwxxhiTIyugjDHGGGNy9P8BKHKrFUtTyKsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.pie(source_top10['cnt'],labels=source_top10['source'])\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "b36dd781",
   "metadata": {},
   "outputs": [],
   "source": [
    "userDF.gender = userDF.gender.replace({'m':'男','f':'女'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "b81a2a41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>screen_name</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>follow_count</th>\n",
       "      <th>gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2823776192</td>\n",
       "      <td>王故里</td>\n",
       "      <td>103万</td>\n",
       "      <td>1673</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2808518423</td>\n",
       "      <td>飛諺評談</td>\n",
       "      <td>8.3万</td>\n",
       "      <td>235</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1644489953</td>\n",
       "      <td>南方都市报</td>\n",
       "      <td>1868.5万</td>\n",
       "      <td>705</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5131917830</td>\n",
       "      <td>刷野制霸</td>\n",
       "      <td>125</td>\n",
       "      <td>116</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2426194884</td>\n",
       "      <td>封跃平律师</td>\n",
       "      <td>401.3万</td>\n",
       "      <td>2184</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id screen_name followers_count follow_count gender\n",
       "0  2823776192         王故里            103万         1673      男\n",
       "1  2808518423        飛諺評談            8.3万          235      男\n",
       "2  1644489953       南方都市报         1868.5万          705      男\n",
       "3  5131917830        刷野制霸             125          116      男\n",
       "4  2426194884       封跃平律师          401.3万         2184      男"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "userDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "be1f1908",
   "metadata": {},
   "outputs": [],
   "source": [
    "gender_cnt = userDF.groupby('gender')['id'].count().reset_index().rename(columns={'id':'cnt'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "09a28fc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gender</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>女</td>\n",
       "      <td>2215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>男</td>\n",
       "      <td>1818</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  gender   cnt\n",
       "0      女  2215\n",
       "1      男  1818"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gender_cnt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "e065ca32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,6))\n",
    "plt.pie(gender_cnt['cnt'],labels=gender_cnt['gender'])\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "a6cf6851",
   "metadata": {},
   "outputs": [],
   "source": [
    "weibo_atttitude_top10 = weiboDF.sort_values(['attitudes_count'],ascending=False)[:10]\n",
    "weibo_comment_top10 = weiboDF.sort_values(['comments_count'],ascending=False)[:10]\n",
    "weibo_repost_top10 = weiboDF.sort_values(['reposts_count'],ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "a5a3d84c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "plt.subplot(1,3,1)\n",
    "sns.barplot(x='screen_name',y='attitudes_count',data=weibo_atttitude_top10)\n",
    "plt.xticks(rotation=60)\n",
    "plt.subplot(1,3,2)\n",
    "sns.barplot(x='screen_name',y='comments_count',data=weibo_comment_top10)\n",
    "plt.xticks(rotation=60)\n",
    "plt.subplot(1,3,3)\n",
    "sns.barplot(x='screen_name',y='reposts_count',data=weibo_repost_top10)\n",
    "plt.xticks(rotation=60)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "ec7ef8dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>screen_name</th>\n",
       "      <th>created_at</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>mid</th>\n",
       "      <th>attitudes_count</th>\n",
       "      <th>comments_count</th>\n",
       "      <th>reposts_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2823776192</td>\n",
       "      <td>王故里</td>\n",
       "      <td>Tue Oct 26 11:05:37 +0800 2021</td>\n",
       "      <td>iPhone 13 Pro Max(远峰蓝色)</td>\n",
       "      <td>#如何看待元气森林被薅羊毛# 元气森林店铺秒杀活动设置错误，有人表示甚至一次性买了三万瓶，官...</td>\n",
       "      <td>4696505108139675</td>\n",
       "      <td>9567</td>\n",
       "      <td>623</td>\n",
       "      <td>1086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2808518423</td>\n",
       "      <td>飛諺評談</td>\n",
       "      <td>Fri Oct 29 09:19:48 +0800 2021</td>\n",
       "      <td>某评论员的iPhone客户端</td>\n",
       "      <td>#元气森林再次回应运营事故#果然不出所料，最终可能还是演变成了事件营销。元气森林第一步为14...</td>\n",
       "      <td>4697565642359968</td>\n",
       "      <td>42</td>\n",
       "      <td>21</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1644489953</td>\n",
       "      <td>南方都市报</td>\n",
       "      <td>Fri Oct 29 17:22:00 +0800 2021</td>\n",
       "      <td>微博 weibo.com</td>\n",
       "      <td>【#元气森林事故订单额达千万# 称价格设错请顾客退款！律师：其无权单方面变更合同】近日，元气...</td>\n",
       "      <td>4697686990652953</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5131917830</td>\n",
       "      <td>刷野制霸</td>\n",
       "      <td>Fri Oct 29 17:21:43 +0800 2021</td>\n",
       "      <td>Android</td>\n",
       "      <td>#元气森林向14万下单用户每人赠送一箱饮料# 有报道说事故订单的损失不止200多万，可能达数...</td>\n",
       "      <td>4697686920661879</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2426194884</td>\n",
       "      <td>封跃平律师</td>\n",
       "      <td>Fri Oct 29 15:42:29 +0800 2021</td>\n",
       "      <td>微博视频号</td>\n",
       "      <td>#元气森林商业信誉如何挽回# 原价79元气泡水仅卖3.5元被买爆，有人一次下单3万箱，元气森...</td>\n",
       "      <td>4697661947775466</td>\n",
       "      <td>66</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id screen_name                      created_at  \\\n",
       "0  2823776192         王故里  Tue Oct 26 11:05:37 +0800 2021   \n",
       "1  2808518423        飛諺評談  Fri Oct 29 09:19:48 +0800 2021   \n",
       "2  1644489953       南方都市报  Fri Oct 29 17:22:00 +0800 2021   \n",
       "3  5131917830        刷野制霸  Fri Oct 29 17:21:43 +0800 2021   \n",
       "4  2426194884       封跃平律师  Fri Oct 29 15:42:29 +0800 2021   \n",
       "\n",
       "                    source                                               text  \\\n",
       "0  iPhone 13 Pro Max(远峰蓝色)  #如何看待元气森林被薅羊毛# 元气森林店铺秒杀活动设置错误，有人表示甚至一次性买了三万瓶，官...   \n",
       "1           某评论员的iPhone客户端  #元气森林再次回应运营事故#果然不出所料，最终可能还是演变成了事件营销。元气森林第一步为14...   \n",
       "2             微博 weibo.com  【#元气森林事故订单额达千万# 称价格设错请顾客退款！律师：其无权单方面变更合同】近日，元气...   \n",
       "3                  Android  #元气森林向14万下单用户每人赠送一箱饮料# 有报道说事故订单的损失不止200多万，可能达数...   \n",
       "4                    微博视频号  #元气森林商业信誉如何挽回# 原价79元气泡水仅卖3.5元被买爆，有人一次下单3万箱，元气森...   \n",
       "\n",
       "                mid  attitudes_count  comments_count  reposts_count  \n",
       "0  4696505108139675             9567             623           1086  \n",
       "1  4697565642359968               42              21             13  \n",
       "2  4697686990652953                0               0              0  \n",
       "3  4697686920661879                0               0              0  \n",
       "4  4697661947775466               66               8             15  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weiboDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "8e31addb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 926 entries, 0 to 925\n",
      "Data columns (total 9 columns):\n",
      " #   Column           Non-Null Count  Dtype \n",
      "---  ------           --------------  ----- \n",
      " 0   id               926 non-null    int64 \n",
      " 1   screen_name      926 non-null    object\n",
      " 2   created_at       926 non-null    object\n",
      " 3   source           926 non-null    object\n",
      " 4   text             926 non-null    object\n",
      " 5   mid              926 non-null    object\n",
      " 6   attitudes_count  926 non-null    int64 \n",
      " 7   comments_count   926 non-null    int64 \n",
      " 8   reposts_count    926 non-null    int64 \n",
      "dtypes: int64(4), object(5)\n",
      "memory usage: 65.2+ KB\n"
     ]
    }
   ],
   "source": [
    "weiboDF.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "2e670c5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "weiboDF.created_at = pd.to_datetime(weiboDF.created_at)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "cbd47c1d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 926 entries, 0 to 925\n",
      "Data columns (total 9 columns):\n",
      " #   Column           Non-Null Count  Dtype                                \n",
      "---  ------           --------------  -----                                \n",
      " 0   id               926 non-null    int64                                \n",
      " 1   screen_name      926 non-null    object                               \n",
      " 2   created_at       926 non-null    datetime64[ns, pytz.FixedOffset(480)]\n",
      " 3   source           926 non-null    object                               \n",
      " 4   text             926 non-null    object                               \n",
      " 5   mid              926 non-null    object                               \n",
      " 6   attitudes_count  926 non-null    int64                                \n",
      " 7   comments_count   926 non-null    int64                                \n",
      " 8   reposts_count    926 non-null    int64                                \n",
      "dtypes: datetime64[ns, pytz.FixedOffset(480)](1), int64(4), object(4)\n",
      "memory usage: 65.2+ KB\n"
     ]
    }
   ],
   "source": [
    "weiboDF.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "ade56bc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      10\n",
       "1      10\n",
       "2      10\n",
       "3      10\n",
       "4      10\n",
       "       ..\n",
       "921    10\n",
       "922    10\n",
       "923    10\n",
       "924    10\n",
       "925    10\n",
       "Name: created_at, Length: 926, dtype: int64"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weiboDF.created_at.apply(lambda x:x.month)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "f1ee0e87",
   "metadata": {},
   "outputs": [],
   "source": [
    "weiboDF['date'] = weiboDF.created_at.astype('str').apply(lambda x:x[:13])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "fd695c0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>iPhone 13 Pro Max(远峰蓝色)</td>\n",
       "      <td>#如何看待元气森林被薅羊毛# 元气森林店铺秒杀活动设置错误，有人表示甚至一次性买了三万瓶，官...</td>\n",
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       "      <td>飛諺評談</td>\n",
       "      <td>2021-10-29 09:19:48+08:00</td>\n",
       "      <td>某评论员的iPhone客户端</td>\n",
       "      <td>#元气森林再次回应运营事故#果然不出所料，最终可能还是演变成了事件营销。元气森林第一步为14...</td>\n",
       "      <td>4697565642359968</td>\n",
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       "      <th>2</th>\n",
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       "      <td>微博 weibo.com</td>\n",
       "      <td>【#元气森林事故订单额达千万# 称价格设错请顾客退款！律师：其无权单方面变更合同】近日，元气...</td>\n",
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       "      <td>Android</td>\n",
       "      <td>#元气森林向14万下单用户每人赠送一箱饮料# 有报道说事故订单的损失不止200多万，可能达数...</td>\n",
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       "      <td>2021-10-29 17</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2426194884</td>\n",
       "      <td>封跃平律师</td>\n",
       "      <td>2021-10-29 15:42:29+08:00</td>\n",
       "      <td>微博视频号</td>\n",
       "      <td>#元气森林商业信誉如何挽回# 原价79元气泡水仅卖3.5元被买爆，有人一次下单3万箱，元气森...</td>\n",
       "      <td>4697661947775466</td>\n",
       "      <td>66</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>2021-10-29 15</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "           id screen_name                created_at                   source  \\\n",
       "0  2823776192         王故里 2021-10-26 11:05:37+08:00  iPhone 13 Pro Max(远峰蓝色)   \n",
       "1  2808518423        飛諺評談 2021-10-29 09:19:48+08:00           某评论员的iPhone客户端   \n",
       "2  1644489953       南方都市报 2021-10-29 17:22:00+08:00             微博 weibo.com   \n",
       "3  5131917830        刷野制霸 2021-10-29 17:21:43+08:00                  Android   \n",
       "4  2426194884       封跃平律师 2021-10-29 15:42:29+08:00                    微博视频号   \n",
       "\n",
       "                                                text               mid  \\\n",
       "0  #如何看待元气森林被薅羊毛# 元气森林店铺秒杀活动设置错误，有人表示甚至一次性买了三万瓶，官...  4696505108139675   \n",
       "1  #元气森林再次回应运营事故#果然不出所料，最终可能还是演变成了事件营销。元气森林第一步为14...  4697565642359968   \n",
       "2  【#元气森林事故订单额达千万# 称价格设错请顾客退款！律师：其无权单方面变更合同】近日，元气...  4697686990652953   \n",
       "3  #元气森林向14万下单用户每人赠送一箱饮料# 有报道说事故订单的损失不止200多万，可能达数...  4697686920661879   \n",
       "4  #元气森林商业信誉如何挽回# 原价79元气泡水仅卖3.5元被买爆，有人一次下单3万箱，元气森...  4697661947775466   \n",
       "\n",
       "   attitudes_count  comments_count  reposts_count           date  \n",
       "0             9567             623           1086  2021-10-26 11  \n",
       "1               42              21             13  2021-10-29 09  \n",
       "2                0               0              0  2021-10-29 17  \n",
       "3                0               0              0  2021-10-29 17  \n",
       "4               66               8             15  2021-10-29 15  "
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weiboDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "cbaab573",
   "metadata": {},
   "outputs": [],
   "source": [
    "date_cnt = weiboDF.groupby('date')['id'].count().reset_index().sort_values('date').rename(columns={'id':'cnt'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "54d751bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2021-10-28 13</td>\n",
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       "      <td>26</td>\n",
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      "text/plain": [
       "            date  cnt\n",
       "0  2021-10-26 11    1\n",
       "1  2021-10-26 18    1\n",
       "2  2021-10-27 18    1\n",
       "3  2021-10-28 13    6\n",
       "4  2021-10-28 14   26"
      ]
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     "execution_count": 91,
     "metadata": {},
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   ],
   "source": [
    "date_cnt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "7214bf22",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "sns.lineplot(x=date_cnt['date'],y=date_cnt['cnt'])\n",
    "plt.xticks(rotation=60)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "8b63f230",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>screen_name</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>follow_count</th>\n",
       "      <th>gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2823776192</td>\n",
       "      <td>王故里</td>\n",
       "      <td>103万</td>\n",
       "      <td>1673</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2808518423</td>\n",
       "      <td>飛諺評談</td>\n",
       "      <td>8.3万</td>\n",
       "      <td>235</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1644489953</td>\n",
       "      <td>南方都市报</td>\n",
       "      <td>1868.5万</td>\n",
       "      <td>705</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5131917830</td>\n",
       "      <td>刷野制霸</td>\n",
       "      <td>125</td>\n",
       "      <td>116</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2426194884</td>\n",
       "      <td>封跃平律师</td>\n",
       "      <td>401.3万</td>\n",
       "      <td>2184</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id screen_name followers_count follow_count gender\n",
       "0  2823776192         王故里            103万         1673      男\n",
       "1  2808518423        飛諺評談            8.3万          235      男\n",
       "2  1644489953       南方都市报         1868.5万          705      男\n",
       "3  5131917830        刷野制霸             125          116      男\n",
       "4  2426194884       封跃平律师          401.3万         2184      男"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "userDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "a060aaad",
   "metadata": {},
   "outputs": [],
   "source": [
    "containsDF = userDF[userDF.followers_count.str.contains('万')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "ac5d3181",
   "metadata": {},
   "outputs": [],
   "source": [
    "userDF.loc[containsDF.index,'followers_count'] = containsDF.followers_count.apply(lambda x: float(x[:-1]) * 10000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "a676119e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>screen_name</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>follow_count</th>\n",
       "      <th>gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2823776192</td>\n",
       "      <td>王故里</td>\n",
       "      <td>1030000.0</td>\n",
       "      <td>1673</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2808518423</td>\n",
       "      <td>飛諺評談</td>\n",
       "      <td>83000.0</td>\n",
       "      <td>235</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1644489953</td>\n",
       "      <td>南方都市报</td>\n",
       "      <td>18685000.0</td>\n",
       "      <td>705</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5131917830</td>\n",
       "      <td>刷野制霸</td>\n",
       "      <td>125</td>\n",
       "      <td>116</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2426194884</td>\n",
       "      <td>封跃平律师</td>\n",
       "      <td>4013000.0</td>\n",
       "      <td>2184</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id screen_name followers_count follow_count gender\n",
       "0  2823776192         王故里       1030000.0         1673      男\n",
       "1  2808518423        飛諺評談         83000.0          235      男\n",
       "2  1644489953       南方都市报      18685000.0          705      男\n",
       "3  5131917830        刷野制霸             125          116      男\n",
       "4  2426194884       封跃平律师       4013000.0         2184      男"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "userDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "e700b19d",
   "metadata": {},
   "outputs": [],
   "source": [
    "userDF = userDF.drop_duplicates('id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "5495d431",
   "metadata": {},
   "outputs": [],
   "source": [
    "yiDF = userDF[userDF.followers_count.astype('str').str.contains('亿')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "02c15e98",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\zzk10\\python37\\lib\\site-packages\\pandas\\core\\indexing.py:1773: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._setitem_single_column(ilocs[0], value, pi)\n"
     ]
    }
   ],
   "source": [
    "userDF.loc[yiDF.index,'followers_count'] = yiDF.followers_count.apply(lambda x: str(float(x[:-1]) * 100000000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "f41d8b38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>screen_name</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>follow_count</th>\n",
       "      <th>gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>5878659096</td>\n",
       "      <td>超话社区</td>\n",
       "      <td>194000000.0</td>\n",
       "      <td>2726</td>\n",
       "      <td>男</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             id screen_name followers_count follow_count gender\n",
       "455  5878659096        超话社区     194000000.0         2726      男"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "userDF.loc[yiDF.index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "b3d3f5a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\zzk10\\python37\\lib\\site-packages\\pandas\\core\\generic.py:5516: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self[name] = value\n"
     ]
    }
   ],
   "source": [
    "userDF.followers_count = userDF.followers_count.astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "df28a5b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "followers_top10 = userDF.sort_values('followers_count',ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "ac47245e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='screen_name',y='followers_count',data=followers_top10)\n",
    "plt.xticks(rotation=60)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6ee73533",
   "metadata": {},
   "outputs": [],
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